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REGRESINIO MODELIO SUDARYMO PAVYZDYS

BUTŲ NUOMOS KAINŲ VILNIAUS MIESTE

EKONOMETRINIS MODELIS

SUDARĖ: II kurso vakarinių studijų ekonomikos spec. studentės Ana Žibul Laima Kasparavičiūtė

BUTŲ NUOMOS KAINŲ VILNIAUS MIESTE
EKONOMETRINIO MODELIO KINTAMIEJI IR DUOMENYS Tikslas. Mūsų darbo tikslas išsiaiškinti nuo ko priklauso butų nuomos kaina Vilniaus mieste ir kiek tam tikri veisniai daro įtaką butų nuomos kainai, t.y. kiek vienam veiksniui pakitus vienu vienetu (ar kitu skaičiuojamu dydžiu), kitiems veiksniams esant tiems ptiems, pakinta butų nuomos kaina. Šiuo tikslu, pasinaudojant nekilnojamojo turto skelbimų portale „ARUODAS“ skelbiamais duomenimis, išrinkome duomenis apie įvairaus dydžio, įvairiuose Vilniaus mikrorajonuose nuomojamus butus. Duomenys. Iš viso ekonometriniam modeliui sudaryti surinkome 192 stebėjimų (žiūr. 1 priedą). Kintamieji: Priklausomasis kintamasis (Y) – butų nuomos kaina; Nepriklausomi kintamieji: Kiekybiniai: Kambarių skaičius (Xkamb.), Buto plotas (Xplotas) Buto statybos metai, t.y buto senumas (Xsen.); Fiktyvūs kintamieji – Prestižinis mikrorajonas ar neprestižinis mikrorajonas, su baldais ar be baldų, yra internetas ar be interneto, yra kabelinė tv ar nėra, langai su stiklo paketais ar paprasti, su buitine technika ar be jos, ir kokiame aukšte butas, t.y. pirmas ar paskutinis, ar kitas aukštas. Prie prestižinių mikrorajonų priskyrėme Antakalnį, Centrą, Senamiestį, Naujamiestį, Užupį bei Žvėryną. Nepriklausomiems fiktyviems kintamiesiems, kurie, mūsų nuomone, turėtų didinti butų nuomos kainą, priskyrėme 1, kitiems – 0. Pagal tai nepriklausomi fiktyvūs kintamieji pasiskirstę taip:
|D prestižinis mikrorajonas – 1 |D kiti rajonai - 0 |Dmraj. |
|D su baldais - 1 |D be baldų - 0 |Dbaldai |
|D su internetu – 1 |D be interneto - 0 |Dinter. |
|D su kabeline – 1 |D be kabelinės - 0 |DkTV |
|D langai su stiklo paketu – 1 |D paprasti langai - 0 |Dlangai |
|D su buitine technika – 1 |D be buitinės technikos – 0 |Dbtech. |
|D ne pirmas ir ne paskutinis aukštas – 1 |D pirmas arba paskutinis aukštas - 0 |Daukštas |

HIPOTEZĖS

Atsižvelgiant į, mūsų nuomone, nepriklausomų kintamųjų galimai daromą įtaką kainai, iškėlėme šias hipotezes: 1. Kuo butas yra senesnis, tai tuo šio buto nuomos kaina mažesnė (jei X sen. didėja, tai Y mažėja). 2. Kuo buto plotas didesnis, tai tuo nuomos kaina didesnė (jei Xplotas didėja, tai Y didėja). 3. Kuo kambarių skaičius didesnis, tuo nuomos kaina didesnė (jei X kamb. Didėja, tai Y didėja). 4. Jei D mraj. – 1, tai Y didėja. 5. Jei D baldai – 1, tai Y didėja. 6. Jei D b.techn. – 1, tai Y didėja. 7. Jei D langai – 1, tai Y didėja. 8. Jei D intern. – 1, tai Y didėja. 9. Jei D kTV – 1, tai Y didėja. 10. Jei D aukštas – 1, tai Y didėja.

II ETAPAS.
GRAFINĖ/STATISTINĖ DUOMENŲ ANALIZĖ

Stebinių statistiniai rodikliai

|Mean |Vidurkis |1515,625 |
|Standard Error |Standartinė paklaida |49,06358205 |
|Median |Mediana |1400 |
|Mode |Moda |1000 |
|Standard Deviation |Standartinis nuokrypis |679,8449354 |
|Sample Variance |Dispersija |462189,1361 |
|Kurtosis |Ekscesas |4,723405155 |
|Skewness |Asimetrija |1,564569786 |
|Range |Variacijos užmojis |4550 |
|Minimum |Minimumas |450 |
|Maximum |Maksimumas |5000 |
|Sum |Suma |291000 |
|Count |Stebėjimų skaičius |192 |

Histograma

[pic]

|Bin |Frequency |
|450,00 |2 |
|661,54 |7 |
|873,08 |14 |
|1084,62 |31 |
|1296,15 |24 |
|1507,69 |42 |
|1719,23 |13 |
|1930,77 |14 |
|2142,31 |18 |
|2353,85 |7 |
|2565,38 |11 |
|2776,92 |1 |
|2988,46 |2 |
|More |3 |

Iš histogramos bei statistinius rodiklius matyti, kad skirstinys yra dešiniašonis, galima sakyti smailiaviršūnis (ekscesas daugiau nei 3). Daugiausia pasikartojanti butų nuomos kaina - apie 1500 Lt. Atliekant tyrimą darysim prielaidą, kad skirstinys yra normalus. Įvertinus stebėjimų duomenis, nustatyta, kad 192 stebėjimų butų nuomos kainos vidurkis yra 1515,62 Lt, standartinis nuokrypis - 679,84. Pagal statistinius duomenis nustatyta, kad trys stebėjimai yra išskirtys arba anomalijos, t.y stebėjimai (Eil. Nr.128; 140; 188), kurių nuomos kaina nepatenka į nustatytą intervalą (-524;3555). Tolimesni skaičiavimai atlikti pašalinus anomalijas, t.y. toliau nagrinėjami tik 189 stebėjimai. Šiame grafike matome, kaip išsidėstę stebiniai. Butų nuomos kainos virš 3500 Lt yra anomalijos.
[pic]

Grafinė nuomos kainos ir ploto priklausomybės analizė

[pic]

Iš grafiko matyti, kad didesnės kvadratūros butų nuomos kaina yra didesnė, nei mažesnių butų. Tačiau 60 ir 80 kv.m. ploto butų nuomos kainos, išskyrus vieno stebinio, išsidėsčiusios panašiai, t.y. tarp 800-2500 Lt.

Grafinė nuomos kainos ir kambarių skaičiaus priklausomybės analizė [pic] Mažiausia nuomos kaina yra 1 kambario butų. 2-3 kambarių butų nuomos kaina yra labai panašiai išsidėsčiusios, išskyrus vieną 3 kambarių butą. Butų su keturiais kambariais nuomos kaina išsidėsčiusi plačiausiai. Priklausomybė tarp butų nuomos kainos ir kambarių skaičiaus yra panaši į butų nuomos kainos ir ploto prikausomybę. Vėliau, atlikus porinės koreliacijos analizę, matysime, kad šie nepriklausomi kintamieji, t.y. Xplotas ir Xkamb. tarpusavyje iš tiesų koreliuoja.

Grafinė nuomos kainos ir buto senumo priklausomybės analizė [pic] Iš grafiko matyti, jog naujų butų, t.y. iki 10 metų senumo, mažiausia nuomos kaina yra apie 800 Lt. Tuo tarpu senesnių, t.y. 15-40 metų senumo butus galima išsinuomoti pigiau. Jų nuomos kainos išsidėsčiusios intervale nuo 450 Lt - 2500 Lt. Senesnių nei 40 metų butų nuomos kaina kyla, ji išsibarsčiusi nuo 1000 Lt iki 3200 Lt. Taigi, pigiausia būtų galima išsinuomoti butą, kuris yra 15-40 metų senumo.

REGRESINIO MODELIO SUDARYMAS

Parenkamas dauginis tiesinis modelis

REGRESINĖ LYGTIS

Pirminė regresinė lygtis: Y= -115,97 – 1,54 Xsen. + 18,85 Xplotas –78,57Xkamb. + -0,41 -1,15 8,54 -1,60 + 421,26Dmraj. + 34,35D baldai + 30,65Dbtechn. + 250,08Dlangai + 46,85Dintern. + 7,73 0,15 0,28 2,81 0,63 + 130,70 DkTV. + 29,19 Daukštas. 0,90 0,49 Dalies nepriklausomų kintamųjų apskaičiuota t reikšmė yra maženė už teorinę, kuri yra lygi 1,97. Tai rodo, kad dalis veiksnių nedaro įtakos butų nuomos kainai. Siekiant iš regresijos pašalinti nereikšmingus veiksnius, atlikome Backward procedūrą (žiūr. 2 priedą). Prieš pradedant šią procedūrą, pirmiausia pašalinome Xkamb., kadangi atlikus porinę koreliaciją šis nepriklausomas kintamasis koreliavo su Xplotas. Pašalinti Xkamb., o ne Xplotas apsisprendėme dėl šio veiksnio silpnesnės koreliacijos su priklausomu kintamuoju Y. Atlikus Backward procedūrą iš regresijos pašalinome statisti6kai nereik6mingus nepriklausomus kintamuosius: Xsen., D baldai, Dbtechn., Dintern., DkTV. bei Daukštas.

Beckward metodu parinktas regresinis modelis: Y= 16 Xplotas + 432 Dmraj. + 333 Dlangai + e. 19,21 8,08 5,27 Koreg. R2 = 0,9522 Atlikus šių veiksnių interkoreliacijos diagnostiką, panaudojant dauginės determinacijos koeficientus, nustatyta, kad visi koreg. R2 yra mažesni nei pagrindinės regresijos lygties koreg. R2, ir artimi 0, tai leidžia teigti, jog regresinis modelis nepasižymi interkoreliacija (žiūr. 3 priedą).

REGRESIJOS REIKŠMINGUMAS Panaudojant FINV funkciją, patikrinome ar mūsų sudaryto butų nuomos kainos modelio regresija yra reikšminga. Apskaičiuota F=1414,42 Teorinė F=2,652 Mūsų atveju, Fapskaičiuota ženkliai didesnė už Fteorinė, tai rodo, kad regresija yra reikšminga. Tai, kad regresija reikšminga, rodo ir koreguotas determinacijos koeficientas, kuris yra artimas 1. Regresijos nepaaiškinta butų nuomos kainos dalis lieka labai nedidelė, t.y. regresijos lygtyje esantys veiksniai iš esmės paaiškina kas lemia butų nuomos kainą. Galutinė butų nuomos kainos regresijos lygtis Y= 16 Xplotas + 420 Dmraj. + 333 Dlangai . 19,21 8,08 5,27 R2 = 0,9502

AUTOKORELIACIJOS DIAGNOSTIKA

GRAFINIS BŪDAS

Butų nuomos kainos regresijos paklaidų sklaida [pic] Atsižvelgiant į tai, jog paklaidos išsidėsčiusios beveik proporcingai virš ir žemiau X ašies, galima teigti, jog paklaidų autokoreliacijos nėra.
Standartizuotų pklaidų sklaida [pic] Nors dalis standartizuotų paklaidų yra virš 2-jų bei žemiau nei 2, tačiau kadangi didžioji dalis jų visgi yra intervale (-2;2), galima teigti, jog paklaidų autokoreliacijos nėra.

Paklaidų sklaida vėluojančių paklaidų atžvilgiu [pic] Paklaidos išsidėsčiusios panašiai tiek teigiamoje, tiek neigiamoje X ir Y ašių pusėje, dauguma intervale nuo -500 iki 500, todėl galima teigti, kad paklaidų autokoreliacijos nėra. Įsitikinti, ar tikrai nėra autokoreliacijos, atlikome Durbin-Watson testą (žiūr. 3 priedą).

DURBIN-WATSON TESTAS

Kai DL < DW < 4-DU, autokoreliacijos nėra. Mūsų nagrinėjamuoju atveju: DW – 1,732 DL = 1,539; DU = 1,813. 4- DU = 4-1,813 = 2,187 1,539 < 1,732 < 2,187 Atlikus Durbin-Watson testą nustatyta, kad autokoreliacijos nėra.

III ETAPAS.
EKONOMINĖ ANALIZĖ

Y= 16 Xplotas + 420 Dmraj. + 333 Dlangai + e. 19,21 8,08 5,27 Koreg. R2 – 0,9522

Atliekant ekonometrinį tyrimą buvo siekiama nustatyti, ar butų nuomos kaina priklauso nuo šių kintamųjų: Xsen., Xplotas, Dmraj., D baldai, Dbtechn., Dlangai, Dintern., DkTV. bei Daukštas. Kaip parodė galutinė regresijos lygtis, butų nuomos kainai statistiškai reikšmingos įtakos nedaro į ekonometrinį modelį įtraukti veiksniai Xsen., D baldai, Dbtechn., Dintern., DkTV. bei Daukštas. Pagal galutinę regresijos lygtį galime daryti šias išvadas: 1. Buto, kurio plotas yra n kvadratinių metrų, nuomos kaina bus 16xn Lt. Pvz. 60 kv. m. vidutinė buto nuoma bus 960 Lt. esant kitiems veiksniams .t.y. rajonui ir langų tipui vienodiems, Kiekvienas papildomas metras prie nuomos kainos vidutiniškai prideda 16Lt. per mėnesį. Mūsų iškelta hipotezė dėl buto ploto daromos įtakos nuomos kainai pasitvirtino. 2 . Hipotezė, jog jei butas yra prestižiniame rajone, tai šio buto kaina vidutiniškai yra didesnė nei to, kuris yra neprestižiniame rajone, taip pat pasitivirtino. Pagal regresinę lygtį tikėtina, kad kitiems veiksniams esant vienodiems, buto, esančio prestižiniame rajone, nuomos kaina bus 420 Lt didesnė nei kituose rajonuose esančių tokio paties ploto ir langų tipo būtų. 3. Trečiasis veiksnys lemiantis buto nuomos kainą yra fiktyvus kintamasis Dlangai. Mūsų hipotezė, kad jei D langai – 1, t.y. su stiklo paketu, tai Y didėja, yra teisinga. Jeigu butas yra su stiklo paketo langais, tai tikėtina, jog jo nuomos kaina yra 333 Lt didesnė nei buto su paprastais langais.

PRIEDAI

Rajonas |Nuomos kaina |Kambarių |Senumas |Plotas |Mikrorajonas |Baldai |Buitinė |Langai |Internetas |Kabelinė |Aukštas | | |(Lt./mėn.) |skaičius |(metai) |(kv.m.) | | |technika | | | | | |Antakalnis |1400 |1 |4 |33 |1 |1 |1 |1 |1 |1 |1 | |Antakalnis |2400 |2 |1 |76 |1 |1 |1 |1 |0 |1 |1 | |Antakalnis |2000 |3 |7 |73 |1 |1 |1 |1 |1 |1 |1 | |Antakalnis |1800 |4 |39 |93 |1 |1 |1 |0 |1 |1 |1 | |Antakalnis |1400 |1 |4 |33 |1 |1 |1 |1 |1 |1 |1 | |Antakalnis |2000 |2 |24 |68 |1 |1 |1 |1 |1 |1 |1 | |Antakalnis |2000 |3 |5 |85 |1 |1 |1 |1 |1 |1 |1 | |Antakalnis |1800 |4 |39 |93 |1 |1 |1 |1 |1 |1 |1 | |Bajorai |1050 |1 |7 |38 |0 |1 |1 |1 |1 |1 |1 | |Bajorai |1300 |2 |2 |65 |0 |1 |1 |1 |1 |1 |1 | |Bajorai |1700 |3 |2 |80 |0 |1 |1 |1 |1 |1 |0 | |Bajorai |1750 |4 |7 |95 |0 |1 |1 |1 |1 |1 |1 | |Bajorai |1500 |1 |2 |33 |0 |1 |0 |1 |1 |1 |1 | |Bajorai |1200 |2 |2 |65 |0 |1 |1 |1 |1 |1 |1 | |Bajorai |1700 |3 |1 |75 |0 |1 |1 |1 |1 |1 |1 | |Bajorai |1900 |4 |1 |80 |0 |1 |1 |1 |1 |1 |0 | |Baltupiai |1100 |1 |1 |41 |0 |1 |1 |1 |1 |1 |0 | |Baltupiai |1300 |2 |7 |71 |0 |1 |1 |1 |0 |0 |1 | |Baltupiai |2500 |3 |6 |90 |0 |1 |1 |1 |1 |1 |1 | |Baltupiai |1100 |4 |29 |70 |0 |1 |1 |0 |0 |0 |1 | |Baltupiai |1200 |1 |35 |33 |0 |1 |1 |1 |1 |1 |1 | |Baltupiai |1200 |2 |9 |50 |0 |1 |1 |1 |1 |1 |0 | |Baltupiai |1100 |3 |32 |64 |0 |1 |1 |1 |1 |1 |0 | |Baltupiai |2500 |4 |31 |78 |0 |1 |1 |1 |1 |1 |1 | |Centras |950 |1 |49 |27 |1 |1 |1 |1 |0 |1 |0 | |Centras |1800 |2 |69 |60 |1 |1 |0 |0 |0 |1 |0 | |Centras |2000 |3 |69 |81 |1 |1 |1 |1 |1 |1 |1 | |Centras |2000 |4 |49 |90 |1 |1 |1 |1 |1 |1 |1 | |Centras |1500 |1 |31 |30 |1 |1 |1 |1 |1 |1 |1 | |Centras |1800 |2 |49 |49 |1 |1 |1 |1 |0 |1 |1 | |Centras |1600 |3 |31 |70 |1 |1 |1 |1 |1 |1 |1 | |Centras |2000 |4 |31 |90 |1 |1 |1 |1 |1 |1 |1 | |Fabijoniškės |550 |1 |14 |41 |0 |1 |1 |0 |1 |1 |1 | |Fabijoniškės |1300 |2 |1 |52 |0 |0 |1 |1 |1 |1 |1 | |Fabijoniškės |900 |3 |20 |61 |0 |1 |0 |1 |1 |1 |1 | |Fabijoniškės |1500 |4 |24 |82 |0 |1 |1 |1 |1 |1 |1 | |Fabijoniškės |1000 |1 |8 |42 |0 |1 |1 |1 |1 |1 |1 | |Fabijoniškės |900 |2 |20 |52 |0 |1 |1 |1 |1 |1 |0 | |Fabijoniškės |1200 |3 |20 |52 |0 |1 |1 |1 |1 |1 |0 | |Fabijoniškės |1500 |4 |24 |82 |0 |1 |1 |1 |1 |1 |1 | |Jeruzalė |1350 |1 |9 |29 |0 |1 |1 |1 |1 |1 |0 | |Jeruzalė |800 |2 |18 |50 |0 |1 |1 |1 |1 |1 |1 | |Jeruzalė |1700 |3 |8 |100 |0 |1 |1 |1 |1 |1 |1 | |Jeruzalė |2200 |4 |12 |119 |0 |1 |1 |1 |1 |1 |1 | |Jeruzalė |1200 |1 |5 |43 |0 |1 |1 |1 |1 |1 |1 | |Jeruzalė |1400 |2 |6 |58 |0 |1 |1 |1 |0 |1 |0 | |Jeruzalė |1800 |3 |8 |74 |0 |1 |1 |1 |1 |1 |1 | |Jeruzalė |3000 |4 |13 |144 |0 |1 |1 |1 |1 |1 |1 | |Justiniškės |800 |1 |23 |36 |0 |1 |1 |1 |1 |1 |1 | |Justiniškės |700 |2 |36 |49 |0 |1 |1 |1 |1 |1 |1 | |Justiniškės |800 |3 |24 |68 |0 |1 |1 |1 |1 |1 |0 | |Justiniškės |1100 |4 |24 |75 |0 |1 |0 |0 |1 |1 |1 | |Justiniškės |700 |1 |23 |36 |0 |1 |1 |1 |0 |1 |1 | |Justiniškės |850 |2 |24 |51 |0 |1 |0 |0 |1 |1 |0 | |Justiniškės |1000 |3 |25 |68 |0 |1 |1 |1 |0 |1 |0 | |Justiniškės |1200 |4 |24 |82 |0 |1 |0 |1 |1 |1 |1 | |Karoliniškės |550 |1 |35 |33 |0 |1 |1 |1 |1 |0 |1 | |Karoliniškės |1200 |2 |1 |61 |0 |1 |1 |1 |0 |1 |1 | |Karoliniškės |1200 |3 |35 |64 |0 |1 |1 |1 |1 |1 |1 | |Karoliniškės |1500 |4 |35 |80 |0 |1 |1 |1 |1 |1 |1 | |Karoliniškės |1000 |1 |29 |33 |0 |1 |1 |1 |1 |1 |1 | |Karoliniškės |1000 |2 |3 |54 |0 |1 |1 |1 |1 |1 |1 | |Karoliniškės |1000 |3 |34 |65 |0 |1 |1 |1 |1 |1 |1 | |Karoliniškės |1400 |4 |35 |80 |0 |1 |1 |1 |1 |1 |0 | |Lazdynai |1000 |1 |39 |34 |0 |1 |1 |1 |1 |1 |1 | |Lazdynai |1000 |2 |39 |48 |0 |1 |1 |1 |1 |1 |1 | |Lazdynai |1200 |3 |14 |64 |0 |1 |1 |1 |1 |1 |1 | |Lazdynai |2800 |4 |14 |133 |0 |1 |1 |1 |1 |1 |1 | |Lazdynai |700 |1 |39 |34 |0 |1 |1 |0 |1 |1 |1 | |Lazdynai |1450 |2 |1 |47 |0 |1 |1 |1 |0 |1 |0 | |Lazdynai |1000 |3 |39 |62 |0 |1 |1 |1 |1 |1 |1 | |Lazdynai |2800 |4 |14 |135 |0 |1 |1 |1 |1 |1 |1 | |Lazdynėliai |1000 |1 |11 |38 |0 |1 |1 |1 |1 |1 |1 | |Lazdynėliai |1000 |2 |10 |65 |0 |1 |1 |1 |1 |1 |1 | |Lazdynėliai |1600 |3 |1 |74 |0 |1 |1 |1 |0 |1 |1 | |Lazdynėliai |1700 |4 |1 |95 |0 |1 |1 |1 |1 |1 |1 | |Lazdynėliai |1000 |1 |10 |55 |0 |1 |1 |1 |1 |1 |1 | |Lazdynėliai |1500 |2 |1 |70 |0 |1 |1 |1 |1 |1 |1 | |Lazdynėliai |2000 |3 |4 |87 |0 |1 |1 |1 |1 |1 |1 | |Lazdynėliai |2100 |4 |1 |100 |0 |1 |1 |1 |1 |1 |1 | |Naujamiestis |700 |1 |24 |30 |1 |1 |1 |0 |0 |1 |1 | |Naujamiestis |1500 |2 |33 |51 |1 |1 |1 |1 |1 |1 |1 | |Naujamiestis |2100 |3 |9 |97 |1 |1 |1 |1 |1 |1 |0 | |Naujamiestis |2100 |4 |51 |102 |1 |1 |1 |1 |0 |1 |1 | |Naujamiestis |600 |1 |24 |22 |1 |1 |0 |0 |1 |1 |1 | |Naujamiestis |1000 |2 |24 |46 |1 |1 |1 |1 |1 |1 |1 | |Naujamiestis |1700 |3 |33 |80 |1 |1 |1 |1 |1 |1 |0 | |Naujamiestis |2200 |4 |38 |102 |1 |1 |1 |1 |1 |1 |0 | |Naujininkai |600 |1 |25 |32 |0 |1 |1 |0 |0 |1 |1 | |Naujininkai |800 |2 |25 |50 |0 |1 |1 |0 |1 |1 |0 | |Naujininkai |900 |3 |20 |75 |0 |1 |1 |1 |0 |1 |0 | |Naujininkai |1400 |4 |25 |85 |0 |1 |1 |1 |1 |1 |1 | |Naujininkai |800 |1 |25 |37 |0 |1 |1 |0 |1 |1 |1 | |Naujininkai |800 |2 |20 |45 |0 |1 |1 |1 |1 |1 |1 | |Naujininkai |1400 |3 |25 |72 |0 |1 |1 |0 |1 |1 |1 | |Naujininkai |1450 |4 |25 |87 |0 |1 |1 |1 |1 |1 |1 | |Pašilaičiai |950 |1 |1 |40 |0 |1 |1 |1 |1 |1 |1 | |Pašilaičiai |1200 |2 |11 |64 |0 |1 |1 |1 |1 |1 |1 | |Pašilaičiai |1400 |3 |2 |74 |0 |1 |1 |1 |1 |1 |1 | |Pašilaičiai |1900 |4 |11 |115 |0 |1 |1 |1 |1 |1 |0 | |Pašilaičiai |1000 |1 |3 |40 |0 |1 |1 |1 |1 |1 |1 | |Pašilaičiai |1300 |2 |1 |56 |0 |1 |1 |1 |1 |1 |1 | |Pašilaičiai |900 |3 |16 |67 |0 |1 |1 |1 |0 |1 |1 | |Pašilaičiai |1900 |4 |11 |106 |0 |1 |1 |1 |1 |1 |1 | |Pilaitė |1200 |1 |1 |41 |0 |1 |1 |1 |1 |1 |0 | |Pilaitė |1200 |2 |2 |60 |0 |1 |1 |1 |1 |1 |1 | |Pilaitė |1150 |3 |17 |71 |0 |1 |1 |1 |1 |1 |1 | |Pilaitė |1000 |4 |17 |89 |0 |1 |1 |1 |1 |1 |1 | |Pilaitė |900 |1 |5 |40 |0 |1 |1 |1 |1 |1 |0 | |Pilaitė |1200 |2 |2 |60 |0 |1 |1 |1 |1 |1 |1 | |Pilaitė |1200 |3 |17 |70 |0 |1 |1 |1 |1 |1 |1 | |Pilaitė |1500 |4 |17 |89 |0 |1 |1 |1 |1 |1 |1 | |Saulėtekis |1400 |1 |1 |40 |0 |1 |1 |1 |1 |1 |1 | |Saulėtekis |2000 |2 |4 |55 |0 |1 |1 |1 |1 |1 |1 | |Saulėtekis |2000 |3 |14 |96 |0 |1 |1 |1 |1 |1 |1 | |Saulėtekis |1800 |4 |10 |100 |0 |1 |1 |1 |1 |1 |1 | |Saulėtekis |1300 |1 |7 |45 |0 |1 |1 |1 |1 |1 |0 | |Saulėtekis |2000 |2 |7 |60 |0 |1 |1 |1 |1 |1 |1 | |Saulėtekis |2500 |3 |15 |95 |0 |1 |1 |1 |1 |1 |1 | |Saulėtekis |1900 |4 |14 |110 |0 |1 |1 |1 |1 |1 |1 | |Senamiestis |1250 |1 |1 |35 |1 |1 |1 |1 |1 |1 |0 | |Senamiestis |1200 |2 |69 |45 |1 |1 |1 |1 |1 |1 |1 | |Senamiestis |3200 |3 |3 |83 |1 |1 |1 |1 |1 |1 |1 | |Senamiestis |2500 |4 |10 |96 |1 |1 |1 |1 |1 |1 |0 | |Senamiestis |1000 |1 |69 |25 |1 |1 |1 |1 |1 |1 |1 | |Senamiestis |2200 |2 |69 |70 |1 |1 |1 |1 |1 |1 |1 | |Senamiestis |2300 |3 |69 |80 |1 |1 |1 |1 |1 |1 |0 | |Senamiestis |5000 |4 |69 |150 |1 |1 |1 |1 |1 |1 |0 | |Šeškinė |700 |1 |26 |36 |0 |1 |0 |0 |0 |1 |1 | |Šeškinė |1100 |2 |26 |50 |0 |1 |1 |1 |1 |1 |1 | |Šeškinė |900 |3 |26 |63 |0 |1 |1 |1 |0 |1 |1 | |Šeškinė |1800 |4 |3 |86 |0 |1 |1 |1 |1 |1 |1 | |Šeškinė |800 |1 |26 |39 |0 |1 |1 |0 |1 |1 |0 | |Šeškinė |900 |2 |26 |50 |0 |1 |1 |1 |1 |1 |1 | |Šeškinė |1000 |3 |26 |65 |0 |1 |1 |1 |1 |1 |1 | |Šeškinė |2300 |4 |26 |82 |0 |1 |1 |1 |1 |1 |1 | |Šiaurės miestelis |1300 |1 |3 |37 |1 |0 |1 |1 |1 |1 |1 | |Šiaurės miestelis |1500 |2 |5 |51 |1 |1 |1 |1 |1 |1 |1 | |Šiaurės miestelis |2500 |3 |2 |70 |1 |1 |1 |1 |1 |1 |1 | |Šiaurės miestelis |4500 |4 |5 |91 |1 |1 |1 |1 |1 |1 |1 | |Šiaurės miestelis |1200 |1 |1 |41 |1 |1 |1 |1 |1 |1 |0 | |Šiaurės miestelis |1400 |2 |7 |51 |1 |1 |1 |1 |1 |1 |1 | |Šiaurės miestelis |2000 |3 |1 |80 |1 |1 |1 |1 |1 |1 |1 | |Šiaurės miestelis |2700 |4 |1 |105 |1 |1 |1 |1 |1 |1 |1 | |Šnipiškės |600 |1 |39 |20 |0 |1 |0 |0 |0 |1 |0 | |Šnipiškės |1900 |2 |95 |56 |0 |1 |1 |1 |1 |1 |1 | |Šnipiškės |2500 |3 |5 |77 |0 |1 |1 |1 |1 |1 |1 | |Šnipiškės |2500 |4 |5 |100 |0 |1 |1 |1 |1 |1 |1 | |Šnipiškės |900 |1 |39 |38 |0 |1 |1 |1 |0 |0 |1 | |Šnipiškės |1350 |2 |2 |48 |0 |1 |1 |1 |1 |1 |0 | |Šnipiškės |1700 |3 |111 |57 |0 |1 |1 |1 |1 |1 |1 | |Šnipiškės |2200 |4 |5 |100 |0 |1 |1 |1 |1 |1 |1 | |Užupis |1100 |1 |69 |30 |1 |1 |1 |1 |1 |1 |0 | |Užupis |1700 |2 |3 |56 |1 |1 |1 |1 |1 |1 |1 | |Užupis |2500 |3 |3 |88 |1 |1 |1 |1 |1 |1 |1 | |Užupis |3200 |4 |69 |105 |1 |1 |1 |1 |1 |1 |0 | |Užupis |1500 |1 |3 |44 |1 |1 |1 |1 |1 |1 |1 | |Užupis |1500 |2 |3 |50 |1 |1 |1 |1 |1 |1 |1 | |Užupis |2500 |3 |3 |65 |1 |1 |1 |1 |1 |1 |1 | |Užupis |1500 |4 |69 |96 |1 |1 |1 |1 |1 |1 |1 | |Verkiai |500 |1 |17 |45 |0 |1 |1 |0 |0 |1 |1 | |Verkiai |1300 |2 |1 |65 |0 |1 |1 |1 |1 |1 |1 | |Verkiai |1450 |3 |17 |60 |0 |1 |1 |1 |1 |1 |1 | |Verkiai |2000 |4 |1 |99 |0 |1 |1 |1 |1 |1 |1 | |Verkiai |700 |1 |17 |45 |0 |1 |1 |1 |1 |1 |1 | |Verkiai |1300 |2 |17 |53 |0 |1 |1 |1 |1 |1 |1 | |Verkiai |1500 |3 |17 |65 |0 |1 |1 |1 |1 |1 |1 | |Verkiai |1900 |4 |1 |100 |0 |1 |0 |1 |0 |0 |0 | |Viršuliškės |600 |1 |31 |33 |0 |1 |1 |0 |0 |1 |1 | |Viršuliškės |1000 |2 |31 |49 |0 |1 |1 |0 |0 |1 |1 | |Viršuliškės |1500 |3 |19 |70 |0 |1 |1 |1 |0 |1 |1 | |Viršuliškės |1500 |4 |31 |75 |0 |1 |1 |1 |1 |1 |0 | |Viršuliškės |900 |1 |31 |33 |0 |1 |1 |0 |0 |1 |1 | |Viršuliškės |1000 |2 |31 |65 |0 |1 |1 |1 |1 |1 |1 | |Viršuliškės |1700 |3 |2 |84 |0 |1 |1 |1 |1 |1 |1 | |Viršuliškės |2000 |4 |2 |100 |0 |1 |1 |1 |1 |1 |1 | |Žirmūnai |1300 |1 |1 |32 |0 |1 |1 |1 |0 |1 |1 | |Žirmūnai |1500 |2 |1 |51 |0 |1 |1 |1 |1 |1 |1 | |Žirmūnai |1300 |3 |27 |74 |0 |1 |1 |1 |1 |1 |0 | |Žirmūnai |1400 |4 |24 |75 |0 |1 |1 |1 |1 |1 |1 | |Žirmūnai |950 |1 |6 |40 |0 |1 |1 |0 |0 |1 |0 | |Žirmūnai |1450 |2 |1 |61 |0 |1 |1 |1 |1 |1 |1 | |Žirmūnai |1700 |3 |6 |70 |0 |1 |1 |1 |1 |1 |1 | |Žirmūnai |1700 |4 |24 |75 |0 |1 |1 |1 |1 |1 |1 | |Žvėrynas |450 |1 |24 |16 |1 |1 |0 |0 |0 |0 |1 | |Žvėrynas |2200 |2 |6 |53 |1 |1 |1 |1 |1 |1 |1 | |Žvėrynas |2000 |3 |6 |68 |1 |1 |1 |1 |1 |1 |1 | |Žvėrynas |3700 |4 |6 |97 |1 |1 |1 |1 |1 |1 |1 | |Žvėrynas |450 |1 |24 |25 |1 |1 |0 |0 |0 |1 |1 | |Žvėrynas |1600 |2 |2 |47 |1 |1 |1 |1 |1 |1 |1 | |Žvėrynas |2000 |3 |6 |68 |1 |1 |1 |1 |1 |1 |1 | |Žvėrynas |2500 |4 |6 |140 |1 |1 |1 |1 |1 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...Cash Flow Assignment Companies are required to prepare a statement of cash flows (SCF) in their annual reports because it contains necessary information for external users, such as lenders and investors, who make economic decisions about the companies. It presents the sources and uses of cash and is a basis for cash flow analysis. Because it shows how much actual cash a company has generated, it presents if and how the company is able to pay for its operations and future growth. Companies produce and consume cash in different ways, so the cash flow statement is divided into three sections: cash flows from operations, financing and investing. Basically, the sections on operations and financing show how the company gets its cash, while the investing section shows how the company spends its cash. The cash flow statement is the newest of the three financial statements; companies have only been required to furnish investors with it since 1988. The cash flow statement is similar to the income statement, except that it dispenses with some of the abstract items found on the income statement (such as depreciation) and focuses on actual cash. Most of the information found on the cash flow statement is contained in either the income statement or the balance sheet, but here it is organized in such a way that it is difficult for companies to use accounting tricks to obscure the facts. The cash flow statement is broken down into three parts: Here you’ll find how much money the company...

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Cash Flow

...4/8/2011 Cash Flows Scribd Upload a Document Search Books, Presentations, Business, Academics... Search Documents Explore Documents Books - Fiction Books - Non-fiction Health & Medicine Brochures/Catalogs Government Docs How-To Guides/Manuals Magazines/Newspapers Recipes/Menus School Work + all categories Featured Recent People Authors Students Researchers Publishers Government & Nonprofits Businesses Musicians Artists & Designers Teachers + all categories Most Followed Popular Sign Up | Log In scribd.com/doc/22806908/Cash-Flows 1/48 4/8/2011 Cash Flows STATEMENT OF CASH FLOWS TRUE-FALSE STATEMENTS 1. The statement of cash flows is a required statement that must be prepared along with an income statement, balance sheet, and retained earnings statement. For external reporting, a company must prepare either an income statement or a statement of cash flows, but not both. A primary objective of the statement of cash flows is to show the income or loss on investing and financing transactions. A statement of cash flows indicates the sources and uses of cash during a period. Operating activities include the cash effects of transactions that create revenues and expenses. In preparing a statement of cash flows, the issuance of debt should be reported separately from the retirement of debt. Noncash investing and financing activities must be reported in the body of a statement of cash flows. The statement of cash flows classifies cash receipts and payments...

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Premium Essay

Cash Flow

...CONCEPTS a. The statement of cash flows details the actual cash generated through a specific time period, usually for fiscal year ending 20XX, for example. The cash flow statement, specifically, identifies the actual cash flowing in and out of the company and reveals how a company spends its money. Conversely, the income statement is based on the accrual method of accounting and will contain revenue, for example, that has not been received or expenses that have not yet been paid. b. The two separate methods to prepare the statement of cash flows is the direct and indirect method. Weis Markets uses the indirect method of accounting due to the fact the company uses the accrual method of accounting and derives data from both the balance sheet and income statement. Most companies, public companies specifically, use the indirect method of accounting as most implement accrual accounting. Smaller companies on a cash basis would use the direct method for statement of cash flows. c. The three sections of the statement of cash flows is investing, operating, and financing activities. d. Operating activities pulls from items on the income statements. Investing activities reports the purchase and/or sale of investments and property, plant, and equipment on the balance sheet. Financing activities reports the issuance and repurchases of company stocks, bonds, and payments of dividends on the balance sheet. e. Cash equivalents are current, highly liquid assets that...

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