PŘÍLOHA A. METODA NEJMENŠÍCH ČTVERCŮ PRODEJ BYTŮ. Příloha A. Metoda nejmenších čtverců Prodej bytů

PŘÍLOHA A. METODA NEJMENŠÍCH ČTVERCŮ PRODEJ BYTŮ

Příloha A Metoda nejmenších čtverců Prodej bytů

i


1 1 2 2.5 3.5 4 4.5 5

2 3 TOT. 7 33 40 1 18 125 144 1 72 73 1 10 35 46 4 1 5 8 8 2 2

Cross-tabulation of Pokoj (rows) against Vlastnictvi (columns) Pearson chi-square test = 39.2872 (18 df, p-value = 0.00260706)

0.5 1 2 2.5 3 3.5 4 4.5 5

1 2 TOT. 1 1 16 27 43 13 127 140 73 73 16 4 20 26 26 5 2 7 6 6 2 2

Cross-tabulation of Pokoj (rows) against Zdivo (columns) Pearson chi-square test = 121.441 (9 df, p-value = 6.77312e-022)

1

1 2 3

2 TOT. 3 3 27 12 39 24 252 276

Cross-tabulation of Vlastnictvi (rows) against Zdivo (columns) Pearson chi-square test = 93.5716 (2 df, p-value = 4.79941e-021)

ii


1 2 3 4 4.5 5

1 6 9 5 2

2 3 2 15 4 24 3 17 2 3 1

4 TOT. 27 50 97 134 79 104 12 19 9 9 1 2

Cross-tabulation of Pokoj (rows) against Stav (columns) Pearson chi-square test = 17.3328 (27 df, p-value = 0.922591)

1 2 3

1 2 1 10 5 11 6

3 4 TOT. 2 3 21 3 39 37 222 276

Cross-tabulation of Vlastnictvi (rows) against Stav (columns) Pearson chi-square test = 98.5048 (6 df, p-value = 5.14523e-019)

1 2

1 2 13 7 9 4

3 4 TOT. 29 2 51 31 223 267

Cross-tabulation of Zdivo (rows) against Stav (columns) Pearson chi-square test = 133.611 (3 df, p-value = 9.01261e-029)

iii


1 1.5 2 2.5 3 3.5 4 4.5 5

0 25 1 43 20 9 12 1 4 1

1 TOT. 19 44 1 96 139 53 73 9 13 25 1 20 24 1 2

Cross-tabulation of Pokoj (rows) against Balkon (columns) Pearson chi-square test = 37.1074 (9 df, p-value = 2.5182e-005)

1 2 3

0 1 TOT. 2 1 3 28 11 39 86 190 276

Cross-tabulation of Vlastnictvi (rows) against Balkon (columns) Pearson chi-square test = 25.5422 (2 df, p-value = 2.84167e-006)

1 2

0 1 TOT. 33 18 51 83 184 267

Cross-tabulation of Zdivo (rows) against Balkon (columns) Pearson chi-square test = 20.8876 (1 df, p-value = 4.87045e-006)

1 2 3 4

0 1 TOT. 12 10 22 6 5 11 41 19 60 57 168 225

Cross-tabulation of Stav (rows) against Balkon (columns) Pearson chi-square test = 42.9854 (3 df, p-value = 2.47864e-009)

iv


0.5 1 1.5 2 2.5 3 3.5 4 5

0 1 TOT. 1 1 49 49 1 1 5 5 128 35 163 24 45 69 3 3 8 16 24 1 2 3

Cross-tabulation of Pokoj (rows) against Terasa (columns) Pearson chi-square test = 87.5309 (9 df, p-value = 5.08778e-015)

1 2 3

0 1 TOT. 2 1 3 39 39 179 97 276

Cross-tabulation of Vlastnictvi (rows) against Terasa (columns) Pearson chi-square test = 19.8057 (2 df, p-value = 5.00309e-005)

1 2

0 1 TOT. 51 51 169 98 267

Cross-tabulation of Zdivo (rows) against Terasa (columns) Pearson chi-square test = 27.0576 (1 df, p-value = 1.97481e-007)

1 2 3 4

0 1 TOT. 22 22 11 11 56 4 60 131 94 225

Cross-tabulation of Stav (rows) against Terasa (columns) Pearson chi-square test = 43.7916 (3 df, p-value = 1.67115e-009)

v


0 1

0 1 TOT. 80 36 116 140 62 202

Cross-tabulation of Balkon (rows) against Terasa (columns) Pearson chi-square test = 0.00402855 (1 df, p-value = 0.949392)

1.5 2.5 3.5 4 4.5 5

0 1 TOT. 142 7 149 90 17 107 35 12 47 6 6 3 4 7 1 1 2

Cross-tabulation of Pokoj (rows) against Lodzie (columns) Pearson chi-square test = 31.994 (9 df, p-value = 0.000199603)

1 2 3

0 1 TOT. 3 3 20 19 39 254 22 276

Cross-tabulation of Vlastnictvi (rows) against Lodzie (columns) Pearson chi-square test = 50.966 (2 df, p-value = 8.56798e-012)

1 2

0 1 TOT. 26 25 51 251 16 267

Cross-tabulation of Zdivo (rows) against Lodzie (columns) Pearson chi-square test = 70.5877 (1 df, p-value = 4.40253e-017)

vi


1 2 3 4

0 1 TOT. 16 6 22 8 3 11 36 24 60 217 8 225

Cross-tabulation of Stav (rows) against Lodzie (columns) Pearson chi-square test = 62.7992 (3 df, p-value = 1.48256e-013)

0 1

0 1 TOT. 77 39 116 200 2 202

Cross-tabulation of Balkon (rows) against Lodzie (columns) Pearson chi-square test = 69.8591 (1 df, p-value = 6.36969e-017)

0 1

0 1 TOT. 180 40 220 97 1 98

Cross-tabulation of Terasa (rows) against Lodzie (columns) Pearson chi-square test = 17.7794 (1 df, p-value = 2.48049e-005)

0.5 1 2 2.5 3 3.5 4 4.5 5

0 1 TOT. 1 1 34 7 41 78 43 121 52 42 94 3 3 21 22 43 6 1 7 6 6 1 1 2

Cross-tabulation of Pokoj (rows) against Sklep (columns) Pearson chi-square test = 26.7938 (9 df, p-value = 0.00151294)

vii


1 2 3

0 1 TOT. 2 1 3 11 28 39 183 93 276

Cross-tabulation of Vlastnictvi (rows) against Sklep (columns) Pearson chi-square test = 21.009 (2 df, p-value = 2.74135e-005)

1 2

0 1 TOT. 19 32 51 177 90 267

Cross-tabulation of Zdivo (rows) against Sklep (columns) Pearson chi-square test = 15.2687 (1 df, p-value = 9.32471e-005)

1 2 3 4

0 11

1 TOT. 11 22 11 11 24 36 60 161 64 225

Cross-tabulation of Stav (rows) against Sklep (columns) Pearson chi-square test = 40.1731 (3 df, p-value = 9.79192e-009)

0 1

0 1 TOT. 62 54 116 134 68 202

Cross-tabulation of Balkon (rows) against Sklep (columns) Pearson chi-square test = 5.17626 (1 df, p-value = 0.0228976)

viii


0 1

0 1 TOT. 111 109 220 85 13 98

Cross-tabulation of Terasa (rows) against Sklep (columns) Pearson chi-square test = 37.7397 (1 df, p-value = 8.08437e-010)

0 1

0 1 TOT. 184 93 277 12 29 41

Cross-tabulation of Lodzie (rows) against Sklep (columns) Pearson chi-square test = 20.8532 (1 df, p-value = 4.95866e-006)

0.5 1 1.5 2 2.5 3 4 4.5 5

0 1 49 4 127 5 92 25 1

1 TOT. 1 49 4 3 130 5 2 94 7 32 1 2 2

Cross-tabulation of Pokoj (rows) against Garaz (columns) Pearson chi-square test = 71.915 (9 df, p-value = 6.40621e-012)

1 2 3

0 1 TOT. 3 3 39 39 262 14 276

Cross-tabulation of Vlastnictvi (rows) against Garaz (columns) Pearson chi-square test = 2.22855 (2 df, p-value = 0.328154)

ix


1 2

0 1 TOT. 50 1 51 254 13 267

Cross-tabulation of Zdivo (rows) against Garaz (columns) Pearson chi-square test = 0.860467 (1 df, p-value = 0.353608)

1 2 3 4

0 21 11 56 216

1 1 4 9

TOT. 22 11 60 225

Cross-tabulation of Stav (rows) against Garaz (columns) Pearson chi-square test = 1.32509 (3 df, p-value = 0.723184)

0 1

0 1 111 5 193 9

TOT. 116 202

Cross-tabulation of Balkon (rows) against Garaz (columns) Pearson chi-square test = 0.00368616 (1 df, p-value = 0.951587)

0 1

0 1 TOT. 210 10 220 94 4 98

Cross-tabulation of Terasa (rows) against Garaz (columns) Pearson chi-square test = 0.0346559 (1 df, p-value = 0.852319)

0 1

0 1 TOT. 266 11 277 38 3 41

Cross-tabulation of Lodzie (rows) against Garaz (columns) Pearson chi-square test = 0.950012 (1 df, p-value = 0.329716)

x


0 1

0 1 TOT. 192 4 196 112 10 122

Cross-tabulation of Sklep (rows) against Garaz (columns) Pearson chi-square test = 6.77057 (1 df, p-value = 0.00926732)

0.5 1 2 2.5 3.5 4 4.5 5

0 1 TOT. 1 1 44 1 45 124 4 128 71 10 81 40 8 48 10 10 3 3 2 2

Cross-tabulation of Pokoj (rows) against Parking (columns) Pearson chi-square test = 47.8093 (9 df, p-value = 2.77242e-007)

1 2 3

0 1 TOT. 3 3 30 9 39 259 17 276

Cross-tabulation of Vlastnictvi (rows) against Parking (columns) Pearson chi-square test = 13.2963 (2 df, p-value = 0.00129639)

1 2

0 1 TOT. 37 14 51 255 12 267

Cross-tabulation of Zdivo (rows) against Parking (columns) Pearson chi-square test = 30.0585 (1 df, p-value = 4.19205e-008)

xi


1 2 3 4

0 14 6 52 220

1 8 5 8 5

TOT. 22 11 60 225

Cross-tabulation of Stav (rows) against Parking (columns) Pearson chi-square test = 56.3935 (3 df, p-value = 3.46225e-012)

0 1

0 1 TOT. 102 14 116 190 12 202

Cross-tabulation of Balkon (rows) against Parking (columns) Pearson chi-square test = 3.68613 (1 df, p-value = 0.0548668)

0 1

0 1 TOT. 199 21 220 93 5 98

Cross-tabulation of Terasa (rows) against Parking (columns) Pearson chi-square test = 1.78301 (1 df, p-value = 0.18178)

0 1

0 1 TOT. 257 20 277 35 6 41

Cross-tabulation of Lodzie (rows) against Parking (columns) Pearson chi-square test = 2.61476 (1 df, p-value = 0.105874)

0 1

0 1 TOT. 185 11 196 107 15 122

Cross-tabulation of Sklep (rows) against Parking (columns) Pearson chi-square test = 4.4731 (1 df, p-value = 0.0344325)

xii


0 1 TOT. 279 25 304 13 1 14

0 1

Cross-tabulation of Garaz (rows) against Parking (columns) Pearson chi-square test = 0.020825 (1 df, p-value = 0.885257)

0 1 1.5 2 2.5 3 4 5

1 6 3 12 1

0.5 4 5

1 1.5 2 5 25

2.5 7

3 5

4 5

4

6

7

59

37 7 1

8 2 1

1

34 20

25

13 9 3 1 2 1 1 1

6 TOT. 46 1 132 3 1 106 27 3

Cross-tabulation of Pokoj (rows) against Vybaveni (columns) Pearson chi-square test = 200.16 (81 df, p-value = 4.50719e-012)

1 2 3

0 x 4 19

0.5 1 1.5 2 2.5 3 x x x 1 x 1 3 6 2 2 6 10 6 13 5 34 130 54

4 5 6 1 x x 6 x x 9 5 1

TOT. 3 39 276

Cross-tabulation of Vlastnictvi (rows) against Vybaveni (columns) Pearson chi-square test = 41.6483 (18 df, p-value = 0.00123803)

1 2

0 0.5 1 1.5 1 3 7 7 11 17 6 6

2 2.5 3 4 3 15 8 7 69 91 52 9

5 6 x x 5 1

TOT. 51 267

Cross-tabulation of Zdivo (rows) against Vybaveni (columns) Pearson chi-square test = 46.5582 (9 df, p-value = 4.74283e-007)

xiii


0 1 2 3 4

7 16

0.5 1 1.5 3 10 1

5

15

2 2.5 9 3 4 4 10 136 13

3

4 5

1 3 11 7 48 6 5

6 TOT. 22 11 60 1 225

Cross-tabulation of Stav (rows) against Vybaveni (columns) Pearson chi-square test = 264.722 (27 df, p-value = 7.04617e-041)

0 0.5 1 1.5 2 9 11 11 13 7 1 5

0 1

2 2.5 3 4 5 20 25 22 11 4 14 118 38 5 1

6 TOT. 1 116 202

Cross-tabulation of Balkon (rows) against Vybaveni (columns) Pearson chi-square test = 71.7476 (9 df, p-value = 6.91043e-012)

0 1

0 1 4

0.5 1 1.5 27 1 25 1

2 2.5 3 4 2 98 49 13 77 11 3

5 6 TOT. 3 1 220 2 98

Cross-tabulation of Terasa (rows) against Vybaveni (columns) Pearson chi-square test = 243.563 (9 df, p-value = 2.27709e-047)

0 1

0 1

0.5 1

1 1.5 2 2.5 3 41 14 151 54 1 13 11 1 8

4 5 6 10 5 1 6

TOT. 277 41

Cross-tabulation of Lodzie (rows) against Vybaveni (columns) Pearson chi-square test = 150.181 (9 df, p-value = 8.08991e-028)

0 1

0 1 3

0.5 4

1 1.5 2 2.5 3 32 10 129 16 19 3 35 44

4 5 6 4 3 1 12 2

Cross-tabulation of Sklep (rows) against Vybaveni (columns) Pearson chi-square test = 121.26 (9 df, p-value = 7.37592e-022)

xiv

TOT. 196 122


0 0.5 1 1.5 1 2 50 1 1

0 1

2 2.5 3 4 5 3 172 56 15 4 6 4 1 1

6 TOT. 1 304 14

Cross-tabulation of Garaz (rows) against Vybaveni (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

0 0.5 1 1.5 1 2 43 1 2 1 7

0 1

2 2.5 3 4 5 9 162 55 13 5 7 6 3

6 TOT. 1 292 26

Cross-tabulation of Parking (rows) against Vybaveni (columns) Pearson chi-square test = 127.476 (9 df, p-value = 3.91494e-023)

1 1.5 2 2.5 3 3.5 4 4.5 5

0 0.5 1 2 5 11 12 2 2 29 1 23 19 4 3 2 4 1

3 5

4 3

5 1

6 1

7 8 9

41 50

9

2

1

28 7 3 3 4 10 11 2 3 1 1 1 1

1

2

4 1 1 1 1

12 TOT. 38 2 1 137 1 84 34 17 3 2

Cross-tabulation of Pokoj (rows) against Patro (columns) Pearson chi-square test = 528.772 (99 df, p-value = 6.41099e-060)

1 2 3

0 0.5 1 1 7 1 70

1

2 3 4 5 1 1 1 11 3 4 2 76 67 31 21 7

6 7

8 9 12

5 2 2

3 1

TOT. 3 39 276

Cross-tabulation of Vlastnictvi (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

xv


1 2

0 0.5 1 1 7 2 8 62

2 3 4 5 6 6 10 3 5 7 71 69 31 21 2

7 8 9 6 2 3 1

12 TOT. 1 51 267

Cross-tabulation of Zdivo (rows) against Patro (columns) Pearson chi-square test = 90.5186 (11 df, p-value = 1.31927e-014)

1 2 3 4

0 0.5 1 6 4

1 3 3 5 58

2 3 4 5 3 1 5 1 3 3 1 8 17 5 7 63 58 24 17

6 3 1 4 1

7 8 9 2 1 2 5 1 1

12 TOT. 22 11 1 60 225

Cross-tabulation of Stav (rows) against Patro (columns) Pearson chi-square test = 119.554 (33 df, p-value = 9.71605e-012)

0 1

0 0.5 5 14 6 55

1 2 3 4 5 16 41 13 14 4 61 38 21 12 5

6 7 4 2 3

8 9 12 2 1 1

TOT. 116 202

Cross-tabulation of Balkon (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

0 1

0 0.5 1 1 51 1 27

2 3 4 5 6 56 44 23 24 8 21 35 11 2 1

7 8 9 7 2 3

12 TOT. 1 220 98

Cross-tabulation of Terasa (rows) against Patro (columns) Pearson chi-square test = 24.4005 (11 df, p-value = 0.0111463)

0 1

0 0.5 8 67 5

1 2 3 4 5 71 65 31 20 7 6 14 3 6 2

6 7 5 1 2 1

8 9 12 2 1 1

TOT. 277 41

Cross-tabulation of Lodzie (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

xvi


0 1

0 0.5 1 3 54 2 6 15

2 3 4 5 6 54 48 16 9 5 23 31 18 17 4

7 8 9 3 3 4 2

12 TOT. 1 196 122

Cross-tabulation of Sklep (rows) against Patro (columns) Pearson chi-square test = 34.6728 (11 df, p-value = 0.000280537)

0 1

0 0.5 1 8 70 1 1

2 3 4 5 6 75 75 30 25 8 2 4 4 1 1

7 8 9 7 2 3

12 TOT. 1 304 14

Cross-tabulation of Garaz (rows) against Patro (columns) Pearson chi-square test = 30.232 (11 df, p-value = 0.00145693)

0 1

0 0.5 1 8 70 1 1

2 3 4 5 6 73 73 31 22 6 4 6 3 4 3

7 8 9 4 2 2 3 1

12 TOT. 1 292 26

Cross-tabulation of Parking (rows) against Patro (columns) Pearson chi-square test = 40.6377 (11 df, p-value = 2.7816e-005)

0 0.5 1 2 2.5 3 4 5 6

0 0.5 1 2 1 1 1 2 7 2 1 4 4 49 1 11 53 2 11 1 4 2

3

4

6 4

9 3

5

7

6

7 8 9

2

1 1 2 1

44 8 1 3 18 12 14 2 7 1 1 1 3 1 1

2 2

2 1

12 TOT. 2 27 26 53 1 126 62 16 5 1

Cross-tabulation of Vybaveni (rows) against Patro (columns) Pearson chi-square test = 413.933 (99 df, p-value = 4.11199e-040)

xvii

PŘÍLOHA A. METODA NEJMENŠÍCH ČTVERCŮ PRODEJ BYTŮ 1 0.5 1 2 2.5 3 3.5 4 4.5 5

2 1

2

3 4 TOT. 9 9 11 18 29 14 42 88 146 2 3 10 30 61 101 1 1 3 15 18 9 9 2 2

Cross-tabulation of Pokoj (rows) against MHD (columns) Pearson chi-square test = 96.455 (27 df, p-value = 9.76001e-010)

1 1 2 3

2

1 3 26

3

4 TOT. 3 3 16 22 39 79 168 276

Cross-tabulation of Vlastnictvi (rows) against MHD (columns) Pearson chi-square test = 6.15276 (6 df, p-value = 0.406297)

1 1 2

2

3 27

3 4 TOT. 20 31 51 75 162 267

Cross-tabulation of Zdivo (rows) against MHD (columns) Pearson chi-square test = 7.50469 (3 df, p-value = 0.0574379)

1 1 2 3 4

2 3

2 2 1 22

3 4 TOT. 7 12 22 2 9 11 25 31 60 61 141 225

Cross-tabulation of Stav (rows) against MHD (columns) Pearson chi-square test = 14.2713 (9 df, p-value = 0.112995)

xviii


0 1

1 3

2 9 18

3 4 TOT. 38 66 116 57 127 202

Cross-tabulation of Balkon (rows) against MHD (columns) Pearson chi-square test = 6.28133 (3 df, p-value = 0.0986967)

0 1

1 2 2 21 1 6

3 4 TOT. 83 114 220 12 79 98

Cross-tabulation of Terasa (rows) against MHD (columns) Pearson chi-square test = 24.9432 (3 df, p-value = 1.58683e-005)

0 1

1 2 2 26 1 1

3 4 TOT. 80 169 277 15 24 41

Cross-tabulation of Lodzie (rows) against MHD (columns) Pearson chi-square test = 3.89184 (3 df, p-value = 0.273382)

0 1

1 2 1 22 2 5

3 4 TOT. 70 103 196 25 90 122

Cross-tabulation of Sklep (rows) against MHD (columns) Pearson chi-square test = 16.9249 (3 df, p-value = 0.000732343)

0 1

1 2 2 25 1 2

3 4 TOT. 93 184 304 2 9 14

Cross-tabulation of Garaz (rows) against MHD (columns) Pearson chi-square test = 7.76782 (3 df, p-value = 0.051062)

xix


0 1

1 2 1 23 2 4

3 4 TOT. 89 179 292 6 14 26

Cross-tabulation of Parking (rows) against MHD (columns) Pearson chi-square test = 15.9123 (3 df, p-value = 0.00118193)

1 0 0.5 1 2 3 4 5 6

2 17

2 4 6 1

3 2 4 10 64 5 7 1 1

4

TOT. 19 4 20 32 108 176 54 65 9 16 3 5 1

Cross-tabulation of Vybaveni (rows) against MHD (columns) Pearson chi-square test = 236.365 (27 df, p-value = 2.48774e-035)

1 0 1 2 3 4 5 6 7 8 9 12

1 1 1

2 5 7 8 5 1 1

3 1 27 27 21 5 6 4 3 1

4 TOT. 6 7 41 73 42 77 50 79 23 34 18 26 4 9 4 7 1 2 3 3 1 1

Cross-tabulation of Patro (rows) against MHD (columns) Pearson chi-square test = 21.9519 (33 df, p-value = 0.928664) Tabulka A.1: Kontingenční tabulky pro prodej bytů

xx


m2 Pokoj Vlastnictvi Zdivo Stav 1.0000 0.8205 0.1073 0.2685 0.2361 m2 1.0000 −0.1002 −0.0186 −0.0598 Pokoj 1.0000 0.4525 0.4907 Vlastnictvi 1.0000 0.5832 Zdivo 1.0000 Stav Balkon Terasa 0.1346 0.5816 0.0042 0.2977 0.2718 0.2157 0.2563 0.2917 0.2671 0.3310 1.0000 −0.0036 1.0000

Lodzie −0.1104 0.1123 −0.3306 −0.4711 −0.3169 −0.4687 −0.2365 1.0000

Parking Vybaveni −0.0850 −0.0045 0.0650 −0.0475 −0.1630 −0.0021 −0.3074 0.0105 −0.4008 0.2449 −0.1077 −0.0664 −0.0749 0.0391 0.0907 0.0054 0.1186 0.2214 −0.0081 0.0728 1.0000 −0.0301 1.0000

Sklep Garaz −0.1421 0.1782 m2 0.1069 0.2538 Pokoj −0.2198 0.0811 Vlastnictvi −0.2191 0.0520 Zdivo −0.2585 −0.0087 Stav −0.1276 0.0034 Balkon −0.3445 −0.0104 Terasa 0.2561 0.0547 Lodzie 1.0000 0.1459 Sklep 1.0000 Garaz

Patro −0.0354 0.1416 −0.2663 −0.4013 −0.3025 −0.2437 −0.1487 0.2216 0.1476 0.0435 0.2241 0.0623 1.0000

MHD 0.1622 0.0539 −0.0530 −0.0663 0.0238 0.0697 0.2140 0.0050 0.1838 −0.0454 −0.1178 0.2941 0.0365 1.0000

m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Tabulka A.2: Korelační matice pro prodej bytů

xxi


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

−2.58197e+006 27676.4 −10187.5 679306. 81851.9 143641. 16853.9 −150141. −89600.9 594300. −162045. −27642.6 105155. 103868. −105554.

391582. 2806.81 78301.7 101901. 124621. 55338.3 80087.0 99356.4 121139. 79248.4 161752. 129075. 35612.3 19989.4 53178.7

−6.5937 9.8605 −0.1301 6.6663 0.6568 2.5957 0.2104 −1.5111 −0.7397 7.4992 −1.0018 −0.2142 2.9528 5.1961 −1.9849

0.0000 0.0000 0.8966 0.0000 0.5118 0.0099 0.8335 0.1318 0.4601 0.0000 0.3172 0.8306 0.0034 0.0000 0.0481

Mean dependent var Sum squared resid R2 F (14, 303) Log-likelihood Schwarz criterion

2349384 9.32e+13 0.725445 57.18612 −4649.394 9385.218

S.D. dependent var 1034754 S.E. of regression 554574.3 Adjusted R2 0.712760 P-value(F ) 2.55e–76 Akaike criterion 9328.788 Hannan–Quinn 9351.326

Tabulka A.3: Odhad metodou OLS pro prodej bytů

xxii


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz Parking Vybaveni Patro

Coefficient

Std. error

t-ratio

p-value

704164. −5733.88 128373. 23706.6 74408.7 61539.9 52896.6 92178.1 11847.9 27539.0 −114805. −18531.3 −6568.10 7964.95

1.25857e+06 11445.5 83582.7 270495. 122668. 66749.1 78737.3 117721. 127622. 229197. 169283. 129210. 54784.9 41552.5

0.5595 −0.5010 1.536 0.08764 0.6066 0.9220 0.6718 0.7830 0.09284 0.1202 −0.6782 −0.1434 −0.1199 0.1917

0.5762 0.6168 0.1256 0.9302 0.5446 0.3573 0.5022 0.4342 0.9261 0.9044 0.4982 0.8861 0.9047 0.8481

Test statistic: F = 8.538707, with p-value = P (F (2, 301) > 8.53871) = 0.000247 Tabulka A.4: RESET test pro prodej bytů

xxiii



6.936 5.462 1.507 2.162 2.321 1.537 2.176 1.704 1.536 1.139 1.293 1.357 1.300 1.393

V IF (j) = 1/(1 − R(j)2 ), where R(j) is the multiple correlation coefficient between variable j and the other independent variables Properties of matrix X ′ X: 1-norm = 2511758.7 Determinant = 1.6501702e+031 Reciprocal condition number = 4.7183614e-007 Tabulka A.5: Test multikolinearity pro prodej bytů

xxiv


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD sq.m2 X2.X3 X2.X4 X2.X5 X2.X6 X2.X7 X2.X8 X2.X9 X2.X10 X2.X11 X2.X12 X2.X13 X2.X14 X2.X15 sq.Pokoj X3.X4 X3.X5 X3.X6 X3.X7 X3.X8 X3.X9

Coefficient

Std. error

t-ratio

p-value

1.70698e+012 −4.67109e+010 5.83566e+011 5.66790e+012 −3.76780e+012 8.66427e+011 1.41719e+012 −4.11607e+012 −6.25412e+011 −3.47317e+010 −1.85933e+013 3.47380e+012 −1.08899e+012 −5.73401e+011 −2.35827e+012 2.29497e+08 −1.09111e+010 −2.75367e+010 3.78999e+010 4.81556e+09 3.81908e+09 −1.35448e+010 2.18470e+010 2.01856e+09 1.57194e+09 −3.26463e+010 6.12419e+09 7.64227e+09 −2.88287e+09 6.59704e+010 8.30000e+011 −3.22696e+011 −2.23868e+011 −5.04008e+011 6.28076e+011 −5.89336e+011

5.71251e+012 5.83612e+010 1.36409e+012 2.54371e+012 1.95462e+012 6.50910e+011 1.67227e+012 3.02184e+012 1.58649e+012 1.41470e+012 8.75900e+012 1.76540e+012 5.37410e+011 2.99345e+011 1.43527e+012 1.60914e+08 8.85978e+09 2.12389e+010 2.80914e+010 7.93829e+09 9.84282e+09 1.22090e+010 2.01439e+010 8.74833e+09 1.79435e+010 1.99987e+010 4.39850e+09 2.23211e+09 7.40656e+09 1.36592e+011 4.81118e+011 5.93652e+011 2.02807e+011 2.80900e+011 3.54563e+011 5.13402e+011

0.2988 −0.8004 0.4278 2.228 −1.928 1.331 0.8475 −1.362 −0.3942 −0.02455 −2.123 1.968 −2.026 −1.916 −1.643 1.426 −1.232 −1.297 1.349 0.6066 0.3880 −1.109 1.085 0.2307 0.08761 −1.632 1.392 3.424 −0.3892 0.4830 1.725 −0.5436 −1.104 −1.794 1.771 −1.148

0.7654 0.4244 0.6692 0.0269 0.0553 0.1846 0.3977 0.1746 0.6938 0.9804 0.0350 0.0504 0.0440 0.0568 0.1019 0.1553 0.2195 0.1962 0.1788 0.5448 0.6984 0.2685 0.2794 0.8177 0.9303 0.1041 0.1653 0.0007 0.6975 0.6296 0.0860 0.5873 0.2709 0.0742 0.0780 0.2523

xxv


X3.X10 X3.X11 X3.X12 X3.X13 X3.X14 X3.X15 sq.Vlastnictvi X4.X5 X4.X6 X4.X7 X4.X8 X4.X9 X4.X10 X4.X12 X4.X13 X4.X14 X4.X15 X5.X6 X5.X7 X5.X9 X5.X10 X5.X11 X5.X12 X5.X13 X5.X14 X5.X15 sq.Stav X6.X7 X6.X8 X6.X9 X6.X10 X6.X11 X6.X12 X6.X13 X6.X14 X6.X15

Coefficient

Std. error

t-ratio

p-value

1.80766e+011 1.32866e+012 −5.73886e+010 −8.86973e+010 −1.07501e+011 −3.68539e+010 −8.95716e+011 −1.00549e+010 −1.97350e+011 −1.07363e+012 1.50794e+012 −4.83259e+011 3.42634e+011 −3.86425e+011 1.08919e+011 1.09533e+011 −3.43708e+011 2.82734e+010 1.01243e+012 3.26899e+011 3.95523e+010 4.00545e+012 −1.17028e+012 −1.47079e+010 7.05459e+010 5.33781e+011 −7.01460e+09 2.57908e+011 −3.16210e+011 2.77997e+011 −1.68276e+011 6.38785e+011 1.84840e+011 8.58492e+09 −4.10075e+010 −2.11410e+010


0.7983 1.628 −0.1141 −0.7147 −1.822 −0.1751 −2.652 −0.03325 −0.9088 −1.974 2.064 −1.228 0.9281 −0.7004 0.9585 1.366 −1.387 0.1419 2.250 0.6607 0.09862 1.946 −1.572 −0.1115 0.7344 2.005 −0.06255 1.423 −0.5261 1.436 −0.6231 0.9965 0.9042 0.08853 −0.9258 −0.1735

0.4256 0.1051 0.9092 0.4756 0.0699 0.8612 0.0086 0.9735 0.3645 0.0497 0.0403 0.2208 0.3545 0.4845 0.3389 0.1734 0.1668 0.8873 0.0255 0.5095 0.9215 0.0530 0.1175 0.9114 0.4635 0.0462 0.9502 0.1564 0.5994 0.1525 0.5339 0.3202 0.3670 0.9295 0.3556 0.8624

xxvi


X7.X8 X7.X9 X7.X10 X7.X11 X7.X12 X7.X13 X7.X14 X7.X15 X8.X9 X8.X10 X8.X11 X8.X12 X8.X13 X8.X14 X8.X15 X9.X10 X9.X11 X9.X12 X9.X13 X9.X14 X9.X15 X10.X11 X10.X12 X10.X13 X10.X14 X10.X15 X11.X12 X11.X13 X11.X14 X11.X15 X12.X13 X12.X14 X12.X15 sq.Vybaveni X13.X14 X13.X15

Coefficient

Std. error

t-ratio

p-value

3.17941e+011 1.44073e+010 7.15330e+011 −1.94738e+012 9.80360e+011 1.06346e+010 −1.42132e+011 −1.84315e+011 −1.40032e+012 −2.41581e+010 −5.77419e+012 5.50716e+011 6.28796e+011 6.26828e+010 −2.67442e+011 2.06642e+011 −3.13628e+012 −3.94804e+011 1.06016e+011 3.17829e+010 −2.54997e+010 −1.90392e+012 1.60014e+010 9.00066e+09 7.26663e+010 −3.76859e+011 6.54937e+012 4.96805e+011 1.06137e+012 1.02497e+012 −2.09447e+011 −1.27841e+011 5.01548e+011 −7.80429e+010 4.00002e+010 2.09200e+011


0.6042 0.02002 2.340 −0.6201 1.301 0.09460 −2.337 −0.9682 −1.230 −0.06059 −1.448 0.6348 3.337 0.7112 −0.7618 0.4318 −1.005 −0.7671 0.7719 0.3323 −0.09593 −2.559 0.03714 0.08880 1.244 −1.799 1.608 1.184 2.279 1.747 −1.159 −1.235 1.916 −2.518 1.521 2.823

0.5464 0.9840 0.0202 0.5359 0.1947 0.9247 0.0204 0.3341 0.2200 0.9517 0.1491 0.5263 0.0010 0.4778 0.4471 0.6663 0.3161 0.4439 0.4410 0.7400 0.9237 0.0112 0.9704 0.9293 0.2150 0.0734 0.1095 0.2377 0.0237 0.0821 0.2476 0.2181 0.0568 0.0126 0.1297 0.0052

xxvii


Coefficient

Std. error

t-ratio

p-value

sq.Patro 1.83565e+010 1.01889e+010 1.802 0.0731 X14.X15 −4.93777e+010 4.69379e+010 −1.052 0.2940 sq.MHD 3.94483e+011 1.20121e+011 3.284 0.0012 Unadjusted R-squared = 0.740195 Test statistic: T R2 = 235.382158, with p-value = P (Chi-square(110) > 235.382158) = 0.000000 Tabulka A.6: Whiteův test pro prodej bytů


Coefficient

Std. error

t-ratio

p-value

−1.62819 0.0304529 −0.196355 0.430376 0.345316 −0.0670375 −0.692068 −0.666145 −0.523126 0.829959 −0.549153 −0.220700 0.127204 0.206045 −0.358185

1.30325 0.00934157 0.260602 0.339146 0.414761 0.184176 0.266544 0.330676 0.403173 0.263753 0.538341 0.429586 0.118524 0.0665284 0.176988

−1.249 3.260 −0.7535 1.269 0.8326 −0.3640 −2.596 −2.014 −1.298 3.147 −1.020 −0.5137 1.073 3.097 −2.024

0.2125 0.0012 0.4518 0.2054 0.4057 0.7161 0.0099 0.0448 0.1954 0.0018 0.3085 0.6078 0.2840 0.0021 0.0439

Explained sum of squares = 220.476 Test statistic: LM = 110.237879, with p-value = P (Chi-square(14) > 110.237879) = 0.000000 Tabulka A.7: Breusch-Paganův test pro prodej bytů

xxviii


Coefficient const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Std. Error

−2.55083e+006 158702. 26092.5 1400.69 17573.1 33553.9 680975. 44992.3 103178. 50759.7 145789. 30528.5 33781.3 35782.6 −118324. 34684.3 −62131.1 53695.6 619951. 32750.3 −228096. 99244.0 −28349.6 39576.0 94585.9 16465.4 99387.6 9807.78 −119063. 25726.5

t-ratio

p-value

−16.0731 18.6284 0.5237 15.1354 2.0327 4.7755 0.9441 −3.4114 −1.1571 18.9296 −2.2983 −0.7163 5.7445 10.1336 −4.6280

0.0000 0.0000 0.6009 0.0000 0.0430 0.0000 0.3459 0.0007 0.2481 0.0000 0.0222 0.4743 0.0000 0.0000 0.0000

Statistics based on the weighted data: Sum squared resid 1.21e+08 S.E. of regression R2 0.955927 Adjusted R2 F (14, 303) 469.4210 P-value(F ) Log-likelihood −2494.805 Akaike criterion Schwarz criterion 5076.040 Hannan–Quinn Statistics based on the original data: Mean dependent var 2349384 S.D. dependent var Sum squared resid 9.38e+13 S.E. of regression

633.0303 0.953890 5.8e–196 5019.609 5042.148 1034754 556451.9

Tabulka A.8: Odhad metodou WLS pro prodej bytů

xxix


Coefficient const m2 Vlastnictvi Zdivo Stav Terasa Sklep Garaz Vybaveni Patro MHD

Std. Error

t-ratio

p-value

−2.60023e+006 182937. −14.2138 0.0000 26824.9 548.349 48.9194 0.0000 689017. 52429.3 13.1418 0.0000 115218. 49549.9 2.3253 0.0207 146996. 31146.3 4.7196 0.0000 −124365. 31329.7 −3.9696 0.0001 616922. 36941.8 16.6998 0.0000 −222331. 96559.1 −2.3025 0.0220 89643.6 17964.0 4.9902 0.0000 94493.1 9391.73 10.0613 0.0000 −113704. 24727.3 −4.5983 0.0000

Statistics based on the weighted data: Sum squared resid 1.21e+08 S.E. of regression 2 R 0.917076 Adjusted R2 F (10, 307) 339.5198 P-value(F ) Log-likelihood −2494.458 Akaike criterion Schwarz criterion 5052.298 Hannan–Quinn Statistics based on the original data: Mean dependent var 2349384 S.D. dependent var Sum squared resid 9.41e+13 S.E. of regression

628.2071 0.914375 1.8e–159 5010.915 5027.444 1034754 553552.4

Tabulka A.9: Odhad metodou WLS pro prodej bytů, zúžený model

xxx

PŘÍLOHA B. METODA NEJMENŠÍCH ČTVERCŮ PRONÁJEM BYTŮ

Příloha B Metoda nejmenších čtverců Pronájem bytů

xxxi


0.5 1 1.5 2 3 3.5 4 4.5

2 2 3 1 5 2 1

3

TOT. 2 29 32 1 31 36 17 19 3 3 1 3 3

Cross-tabulation of Pokoj (rows) against Vlastnictvi (columns) Pearson chi-square test = 25.6327 (8 df, p-value = 0.00121356)

0.5 1 1.5 2 3 3.5 4 4.5

1 1 5 3 3 1 1

2

TOT. 1 28 33 3 31 34 18 19 3 3 1 3 3

Cross-tabulation of Pokoj (rows) against Zdivo (columns) Pearson chi-square test = 32.8286 (8 df, p-value = 6.61243e-005)

2 3

1 2 TOT. 8 6 14 6 77 83

Cross-tabulation of Vlastnictvi (rows) against Zdivo (columns) Pearson chi-square test = 24.1666 (1 df, p-value = 8.83515e-007)

xxxii


0.5 1 1.5 2 3 3.5 4 4.5

1 1 1 1 6 2 1 1

2

3

2 19 2 14 2 1

9 1

4

TOT. 1 11 33 1 14 36 2 8 20 2 1 2

Cross-tabulation of Pokoj (rows) against Stav (columns) Pearson chi-square test = 41.3292 (24 df, p-value = 0.0153235)

2 3

1 2 5 1 8 6

3 4 TOT. 6 2 14 37 32 83

Cross-tabulation of Vlastnictvi (rows) against Stav (columns) Pearson chi-square test = 8.09864 (3 df, p-value = 0.0440165)

1 2

1 2 5 1 8 6

3 4 TOT. 7 1 14 36 33 83

Cross-tabulation of Zdivo (rows) against Stav (columns) Pearson chi-square test = 9.83218 (3 df, p-value = 0.0200479)

0.5 1 2 3 3.5 4.5

0 1 TOT. 2 2 23 5 28 29 6 35 16 11 27 1 1 2 2 4

Cross-tabulation of Pokoj (rows) against Balkon (columns) Pearson chi-square test = 7.86643 (8 df, p-value = 0.446626)

xxxiii


2 3

0 1 10 4 63 20

TOT. 14 83

Cross-tabulation of Vlastnictvi (rows) against Balkon (columns) Pearson chi-square test = 0.128836 (1 df, p-value = 0.719642)

1 2

0 1 10 4 63 20

TOT. 14 83

Cross-tabulation of Zdivo (rows) against Balkon (columns) Pearson chi-square test = 0.128836 (1 df, p-value = 0.719642)

1 2 3 4

0 1 10 3 4 3 32 11 27 7

TOT. 13 7 43 34

Cross-tabulation of Stav (rows) against Balkon (columns) Pearson chi-square test = 1.58432 (3 df, p-value = 0.662951)

0.5 1 1.5 2 2.5 3 3.5 4 4.5

0 1 2 44 16 1 10 1

1 TOT. 1 2 2 46 5 21 1 8 18 4 4 1 3 3

Cross-tabulation of Pokoj (rows) against Terasa (columns) Pearson chi-square test = 39.0234 (8 df, p-value = 4.86652e-006)

xxxiv


2 3

0 1 12 2 66 17

TOT. 14 83

Cross-tabulation of Vlastnictvi (rows) against Terasa (columns) Pearson chi-square test = 0.292 (1 df, p-value = 0.588942)

1 2

0 1 14 64 19

TOT. 14 83

Cross-tabulation of Zdivo (rows) against Terasa (columns) Pearson chi-square test = 3.98548 (1 df, p-value = 0.045894)

1 2 3 4

0 10 7 36 25

1 TOT. 3 13 7 7 43 9 34

Cross-tabulation of Stav (rows) against Terasa (columns) Pearson chi-square test = 3.1271 (3 df, p-value = 0.372441)

0 1

0 1 55 18 23 1

TOT. 73 24

Cross-tabulation of Balkon (rows) against Terasa (columns) Pearson chi-square test = 4.8148 (1 df, p-value = 0.0282163)

xxxv


0.5 1 2 3 3.5 4.5

0 1 29 32 20 1 4

1 TOT. 1 2 31 7 39 1 21 1 4

Cross-tabulation of Pokoj (rows) against Lodzie (columns) Pearson chi-square test = 4.34905 (8 df, p-value = 0.824338)

2 3

0 1 TOT. 11 3 14 76 7 83

Cross-tabulation of Vlastnictvi (rows) against Lodzie (columns) Pearson chi-square test = 2.18776 (1 df, p-value = 0.139111)

1 2

0 1 TOT. 10 4 14 77 6 83

Cross-tabulation of Zdivo (rows) against Lodzie (columns) Pearson chi-square test = 5.90133 (1 df, p-value = 0.0151295)

1 2 3 4

0 12 7 40 28

1 TOT. 1 13 7 3 43 6 34

Cross-tabulation of Stav (rows) against Lodzie (columns) Pearson chi-square test = 3.3972 (3 df, p-value = 0.334341)

xxxvi


0 1

0 1 63 10 24

TOT. 73 24

Cross-tabulation of Balkon (rows) against Lodzie (columns) Pearson chi-square test = 3.66556 (1 df, p-value = 0.0555478)

0 1

0 1 TOT. 69 9 78 18 1 19

Cross-tabulation of Terasa (rows) against Lodzie (columns) Pearson chi-square test = 0.650684 (1 df, p-value = 0.419868)

0.5 1 2 2.5 3 4 4.5

0 1 TOT. 1 1 22 5 27 25 18 43 1 1 15 4 19 2 1 3 1 2 3

Cross-tabulation of Pokoj (rows) against Sklep (columns) Pearson chi-square test = 7.91681 (8 df, p-value = 0.441638)

2 3

0 1 7 7 60 23

TOT. 14 83

Cross-tabulation of Vlastnictvi (rows) against Sklep (columns) Pearson chi-square test = 2.78592 (1 df, p-value = 0.0950959)

xxxvii


1 2

0 1 4 10 63 20

TOT. 14 83

Cross-tabulation of Zdivo (rows) against Sklep (columns) Pearson chi-square test = 12.563 (1 df, p-value = 0.00039345)

1 2 3 4

0 1 10 3 2 5 33 10 22 12

TOT. 13 7 43 34

Cross-tabulation of Stav (rows) against Sklep (columns) Pearson chi-square test = 7.2382 (3 df, p-value = 0.064681)

0 1

0 1 55 18 12 12

TOT. 73 24

Cross-tabulation of Balkon (rows) against Sklep (columns) Pearson chi-square test = 5.4301 (1 df, p-value = 0.0197926)

0 1

0 1 56 22 11 8

TOT. 78 19

Cross-tabulation of Terasa (rows) against Sklep (columns) Pearson chi-square test = 1.38185 (1 df, p-value = 0.239786)

0 1

0 1 61 26 6 4

TOT. 87 10

Cross-tabulation of Lodzie (rows) against Sklep (columns) Pearson chi-square test = 0.429558 (1 df, p-value = 0.512206)

xxxviii


0.5 1 1.5 2 3 3.5 4.5

0 1 1 48 14 11 9 2

1 TOT. 1 1 1 49 6 20 11 2 11 2 4

Cross-tabulation of Pokoj (rows) against Garaz (columns) Pearson chi-square test = 19.2618 (8 df, p-value = 0.0135205)

2 3

0 1 14 72 11

TOT. 14 83

Cross-tabulation of Vlastnictvi (rows) against Garaz (columns) Pearson chi-square test = 2.09274 (1 df, p-value = 0.148)

1 2

0 1 14 72 11

TOT. 14 83

Cross-tabulation of Zdivo (rows) against Garaz (columns) Pearson chi-square test = 2.09274 (1 df, p-value = 0.148)

1 2 3 4

0 12 7 40 27

1 TOT. 1 13 7 3 43 7 34

Cross-tabulation of Stav (rows) against Garaz (columns) Pearson chi-square test = 4.77392 (3 df, p-value = 0.189121)

xxxix


0 1

0 1 TOT. 66 7 73 20 4 24

Cross-tabulation of Balkon (rows) against Garaz (columns) Pearson chi-square test = 0.899891 (1 df, p-value = 0.342811)

0 1

0 1 TOT. 72 6 78 14 5 19

Cross-tabulation of Terasa (rows) against Garaz (columns) Pearson chi-square test = 5.27048 (1 df, p-value = 0.02169)

0 1

0 1 77 10 9 1

TOT. 87 10

Cross-tabulation of Lodzie (rows) against Garaz (columns) Pearson chi-square test = 0.0199181 (1 df, p-value = 0.887766)

0 1

0 1 TOT. 61 6 67 25 5 30

Cross-tabulation of Sklep (rows) against Garaz (columns) Pearson chi-square test = 1.2256 (1 df, p-value = 0.268265)

xl


0.5 1 1.5 2 3 3.5 4 4.5

0 3 28 15 10 17 1 1 2

1 TOT. 3 1 29 7 22 7 17 2 19 2 3 1 1 3

Cross-tabulation of Pokoj (rows) against Parking (columns) Pearson chi-square test = 17.7035 (8 df, p-value = 0.0235624)

2 3

0 1 13 1 64 19

TOT. 14 83

Cross-tabulation of Vlastnictvi (rows) against Parking (columns) Pearson chi-square test = 1.81529 (1 df, p-value = 0.177874)

1 2

0 1 11 3 66 17

TOT. 14 83

Cross-tabulation of Zdivo (rows) against Parking (columns) Pearson chi-square test = 0.00655889 (1 df, p-value = 0.935452)

1 2 3 4

0 1 11 2 7 36 7 23 11

TOT. 13 7 43 34

Cross-tabulation of Stav (rows) against Parking (columns) Pearson chi-square test = 5.39086 (3 df, p-value = 0.145314)

xli


0 1

0 1 60 13 17 7

TOT. 73 24

Cross-tabulation of Balkon (rows) against Parking (columns) Pearson chi-square test = 1.42372 (1 df, p-value = 0.232793)

0 1

0 1 63 15 14 5

TOT. 78 19

Cross-tabulation of Terasa (rows) against Parking (columns) Pearson chi-square test = 0.468577 (1 df, p-value = 0.493642)

0 1

0 1 69 18 8 2

TOT. 87 10

Cross-tabulation of Lodzie (rows) against Parking (columns) Pearson chi-square test = 0.00260636 (1 df, p-value = 0.959284)

0 1

0 1 55 12 22 8

TOT. 67 30

Cross-tabulation of Sklep (rows) against Parking (columns) Pearson chi-square test = 0.970689 (1 df, p-value = 0.324508)

0 1

0 1 68 18 9 2

TOT. 86 11

Cross-tabulation of Garaz (rows) against Parking (columns) Pearson chi-square test = 0.0450097 (1 df, p-value = 0.831986)

xlii


0 2 4

1 2 2.5 3 3.5 4.5

1 2 5 6 2 6 1 1 2 3

3 12 11 1

4 5 7 2

5 2 8 4

5

2 2 1

6 TOT. 32 38 1 9 3 1 11 1 4

Cross-tabulation of Pokoj (rows) against Vybaveni (columns) Pearson chi-square test = 43.9855 (48 df, p-value = 0.638013)

2 3

0 3 3

1

2 3 3 3 8 15 26

4 5 6 TOT. 2 3 14 16 12 3 83

Cross-tabulation of Vlastnictvi (rows) against Vybaveni (columns) Pearson chi-square test = 9.00372 (6 df, p-value = 0.173369)

1 2

0 4 2

1

2 3 2 5 8 16 24

4

5 6 TOT. 3 14 18 12 3 83

Cross-tabulation of Zdivo (rows) against Vybaveni (columns) Pearson chi-square test = 18.8693 (6 df, p-value = 0.0043901)

1 2 3 4

0 1 2 3 8 1

2 3 4 5 5 5 1 2 4 1 8 15 7 2 3 5 10 12

6 TOT. 13 7 43 3 34

Cross-tabulation of Stav (rows) against Vybaveni (columns) Pearson chi-square test = 46.6864 (18 df, p-value = 0.000235401)

xliii


0 1

0 3 3

1 2 3 6 16 21 2 2 8

4 5 6 TOT. 13 11 3 73 5 4 24

Cross-tabulation of Balkon (rows) against Vybaveni (columns) Pearson chi-square test = 5.08328 (6 df, p-value = 0.533178)

0 1

0 6

1 2 3 7 15 25 1 3 4

4 5 6 TOT. 12 12 1 78 6 3 2 19

Cross-tabulation of Terasa (rows) against Vybaveni (columns) Pearson chi-square test = 8.8148 (6 df, p-value = 0.184265)

0 1

0 5 1

1 2 3 8 17 27 1 2

4 5 6 TOT. 15 12 3 87 3 3 10

Cross-tabulation of Lodzie (rows) against Vybaveni (columns) Pearson chi-square test = 4.64205 (6 df, p-value = 0.590471)

0 1

0 1 2 7 4 1

2 3 4 5 14 20 16 7 4 9 2 8

6 TOT. 1 67 2 30

Cross-tabulation of Sklep (rows) against Vybaveni (columns) Pearson chi-square test = 14.1253 (6 df, p-value = 0.0282669)

0 1

0 6

1 2 3 8 18 25 4

4 5 6 TOT. 14 13 2 86 4 2 1 11

Cross-tabulation of Garaz (rows) against Vybaveni (columns) Pearson chi-square test = 7.88914 (6 df, p-value = 0.246338)

xliv


0 1

0 1 5 7 1 1

2 3 4 5 17 22 15 9 1 7 3 6

6 TOT. 2 77 1 20

Cross-tabulation of Parking (rows) against Vybaveni (columns) Pearson chi-square test = 7.00481 (6 df, p-value = 0.320402)

1 1.5 2 2.5 3 3.5 4.5

0 0.5

−0.5 1

1 1 2

1 2 3 4 11 11 1

5 6 7 2 1

8 2 3 4

1 8

4 1 4 5

1 1 6 2

4 2

2 1 1

2 1

8 12 TOT. 27 1 17 2 1 32 3 13 4

Cross-tabulation of Pokoj (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

−0.5 2 3

0 1 6

0.5 6

1 2 3 4 1 3 1 2 19 23 11 5

5 6 7 2 2 10 2

8 12 TOT. 2 14 1 83

Cross-tabulation of Vlastnictvi (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

−0.5 1 2

0

0.5

5

8

1 2 3 4 1 4 1 1 19 22 11 6

5 6 7 2 1 1 10 1 1

8 12 TOT. 2 1 14 83

Cross-tabulation of Zdivo (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

xlv


−0.5 1 2 3 4

1

0 0.5 2 5 4

1 2 3 4 3 3 1 5 8 9 10 3 5 14 2 3

5 6 2 2 4 1 4 1

7 8 12 1 1 2 1

TOT. 13 7 43 34

Cross-tabulation of Stav (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

−0.5 0 1

0 0.5 8 5

1 2 3 4 14 20 8 6 6 6 4 1

5 6 8 4 2

7 8 12 1 2 1 1

TOT. 73 24

Cross-tabulation of Balkon (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

−0.5 0 1

1

0 0.5 10 1

1 2 3 4 18 19 6 7 3 7 6

5 6 7 11 2 2 1

8 12 TOT. 2 1 78 19

Cross-tabulation of Terasa (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

−0.5 0 1

0 0.5 1 2 4 9 19 23 1 3

3 4 5 12 5 9 2 3

6 7 8 2 2 1 1

12 TOT. 1 87 10

Cross-tabulation of Lodzie (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

−0.5 0 1

0 0.5 7 6

1 2 3 4 14 16 7 6 6 10 5 1

5 6 7 1 5 1

7 8 12 1 1 1 1 1

TOT. 67 30

Cross-tabulation of Sklep (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

xlvi


−0.5 0 1

0 6

0.5 1 2 3 4 7 18 21 10 5 2 5 2 2

5 6 7 12 2 2

8 12 TOT. 2 1 86 11

Cross-tabulation of Garaz (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

−0.5 0 1

0 0.5 1 2 4 8 16 20 1 4 6

3 4 5 9 6 10 3 1 2

6 7 8 1 1 2 1 1

12 TOT. 77 1 20

Cross-tabulation of Parking (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

−0.5 0 0 1 2 3 4 5 6

3 4 1 2 1

0.5

2

1 1

2 1 3 3 5 11 5 3 6 2 4 2

3 1 2 1 5 2 1

4 5 1 1 1 1 1 2 1

3 2 3 3

6 7 1

1 1 1

8 12 TOT. 6 8 1 18 1 1 29 18 15 3

Cross-tabulation of Vybaveni (rows) against Patro (columns) Pearson chi-square test not computed: some expected frequencies were less than 1e-007

1 2 2.5 3 3.5 4.5

1 2 1 2

3 4 TOT. 6 27 34 8 29 37 1 3 4 4 8 11 11 3 1 4

Cross-tabulation of Pokoj (rows) against MHD (columns) Pearson chi-square test = 80.3816 (24 df, p-value = 5.2887e-008)

xlvii


1 2 2 3

1 2

3 4 TOT. 5 9 14 17 63 83

Cross-tabulation of Vlastnictvi (rows) against MHD (columns) Pearson chi-square test = 1.94937 (3 df, p-value = 0.582981)

1 2 1 2

1 2

3 4 TOT. 5 9 14 17 63 83

Cross-tabulation of Zdivo (rows) against MHD (columns) Pearson chi-square test = 1.94937 (3 df, p-value = 0.582981)

1 1 2 3 4

1

2 3 4 3 10 5 2 8 34 2 6 26

TOT. 13 7 43 34

Cross-tabulation of Stav (rows) against MHD (columns) Pearson chi-square test = 15.1291 (9 df, p-value = 0.0874504)

0 1

1 2 1 2

3 4 TOT. 12 58 73 10 14 24

Cross-tabulation of Balkon (rows) against MHD (columns) Pearson chi-square test = 7.14017 (3 df, p-value = 0.0675619)

1 2 0 1

1 2

3 4 TOT. 18 60 78 4 12 19

Cross-tabulation of Terasa (rows) against MHD (columns) Pearson chi-square test = 12.7334 (3 df, p-value = 0.00525007)

xlviii


0 1

1 2 1 2

3 4 TOT. 19 65 87 3 7 10

Cross-tabulation of Lodzie (rows) against MHD (columns) Pearson chi-square test = 0.635039 (3 df, p-value = 0.888366)

0 1

1 2 1 1 1

3 4 TOT. 12 54 67 10 18 30

Cross-tabulation of Sklep (rows) against MHD (columns) Pearson chi-square test = 5.93143 (3 df, p-value = 0.114994)

0 1

1 2 2 1

3 4 TOT. 21 63 86 1 9 11

Cross-tabulation of Garaz (rows) against MHD (columns) Pearson chi-square test = 9.18056 (3 df, p-value = 0.0269842)

0 1

1 2 1 2

3 4 TOT. 16 60 77 6 12 20

Cross-tabulation of Parking (rows) against MHD (columns) Pearson chi-square test = 9.24191 (3 df, p-value = 0.0262416)

xlix


1 0 1 2 3 4 5 6

1

2 3 3

4 3 8 16 19 15 9 2

2 1 8 3 1 5 1

TOT. 6 8 18 29 18 15 3

Cross-tabulation of Vybaveni (rows) against MHD (columns) Pearson chi-square test = 14.2384 (18 df, p-value = 0.713422)

0 0.5 1 2 3 4 5 6 7 8 12

1 2

3

1

5 5 4 2 3 1 2

1 1

4 TOT. 6 6 7 7 14 20 21 26 6 12 5 7 9 12 1 2 2 2 2 1 1

Cross-tabulation of Patro (rows) against MHD (columns) Pearson chi-square test = 26.2585 (33 df, p-value = 0.791183) Tabulka B.1: Kontingenční tabulky pro pronájem bytů

l


m2 Pokoj Vlastnictvi Zdivo Stav 1.0000 0.7977 0.1061 0.2429 0.0260 m2 1.0000 0.0009 0.0901 −0.1784 Pokoj 1.0000 0.4991 0.2740 Vlastnictvi 1.0000 0.3039 Zdivo 1.0000 Stav Balkon Terasa −0.0554 0.5136 0.0679 0.3129 −0.0364 0.0549 −0.0364 0.2027 −0.0548 0.0744 1.0000 −0.2228 1.0000

Lodzie Sklep Garaz −0.1169 0.0043 0.3355 −0.1431 −0.0112 0.1686 −0.1502 −0.1695 0.1469 −0.2467 −0.3599 0.1469 0.1349 0.0157 0.1623 −0.1944 0.2366 0.0963 −0.0819 0.1194 0.2331 1.0000 0.0665 −0.0143 1.0000 0.1124 1.0000

Parking Vybaveni 0.1015 0.2414 0.1206 0.1881 0.1368 0.0944 −0.0082 0.1744 0.1768 0.4088 0.1212 −0.0527 0.0695 0.2129 −0.0052 0.1036 0.1000 0.0677 −0.0215 0.2312 1.0000 0.1905 1.0000

Patro −0.0205 0.0031 −0.3011 −0.4248 −0.0867 0.1247 −0.1152 0.1942 0.1429 −0.0358 0.1486 0.0761 1.0000

MHD −0.3648 −0.1816 0.0427 0.0427 0.0245 −0.1207 −0.2471 −0.0006 −0.2406 −0.0414 −0.1832 −0.0943 −0.1058 1.0000

m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz


Tabulka B.2: Korelační matice pro pronájem bytů

li



Coefficient

Std. Error

t-ratio

p-value

−6906.74 47.0334 1622.05 1637.29 −350.927 −931.826 1982.46 1758.17 2018.95 −881.699 2490.00 409.902 409.509 105.402 2087.84

4268.91 24.0632 637.328 1095.72 1313.50 413.871 869.563 1022.82 1158.23 823.264 1153.15 862.399 260.016 175.288 681.598

−1.6179 1.9546 2.5451 1.4943 −0.2672 −2.2515 2.2798 1.7189 1.7431 −1.0710 2.1593 0.4753 1.5749 0.6013 3.0632

0.1095 0.0540 0.0128 0.1389 0.7900 0.0270 0.0252 0.0894 0.0851 0.2873 0.0337 0.6358 0.1191 0.5493 0.0030


10367.11 8.09e+08 0.621003 9.597179 −910.5410 1889.703

S.D. dependent var 4714.400 S.E. of regression 3140.314 Adjusted R2 0.556296 P-value(F ) 3.57e–12 Akaike criterion 1851.082 Hannan–Quinn 1866.698

Tabulka B.3: Odhad metodou OLS pro pronájem bytů

lii


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD yhat2 yhat3

Coefficient

Std. error

t-ratio

p-value

−29169.6 134.954 6183.53 5239.56 −224.302 −2406.49 5137.88 4498.42 6382.53 −2137.47 7261.05 1416.65 1211.94 470.930 6439.10 −0.000264937 8.43061e-09

9057.40 39.7028 1434.94 1493.11 878.912 774.589 1647.19 1668.46 1679.41 845.110 2233.42 569.531 368.781 122.431 1779.95 6.30540e-05 1.44634e-09

−3.221 3.399 4.309 3.509 −0.2552 −3.107 3.119 2.696 3.800 −2.529 3.251 2.487 3.286 3.846 3.618 −4.202 5.829

0.0019 0.0011 4.62e-05 0.0007 0.7992 0.0026 0.0025 0.0085 0.0003 0.0134 0.0017 0.0149 0.0015 0.0002 0.0005 6.84e-05 1.13e-07

Test statistic: F = 80.803487, with p-value = P (F (2, 80) > 80.8035) = 6.3e-020 Tabulka B.4: RESET test pro pronájem bytů

liii



5.118 3.890 1.458 2.096 1.615 1.385 1.621 1.220 1.424 1.315 1.197 1.431 1.378 1.429

V IF (j) = 1/(1 − R(j)2 ), where R(j) is the multiple correlation coefficient between variable j and the other independent variables Properties of matrix X ′ X: 1-norm = 580528.56 Determinant = 4.9731518e+024 Reciprocal condition number = 6.088285e-007 Tabulka B.5: Test multikolinearity pro pronájem bytů

liv


Coefficient const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD sq.m2 sq.Pokoj sq.Stav sq.Vybaveni sq.Patro sq.MHD

Std. error

−1.44793e+08 1.20628e+08 −708398. 1.00169e+06 984759. 2.42722e+07 4.91391e+06 1.17400e+07 −8.78282e+06 1.48697e+07 −4.08791e+07 1.98242e+07 2.46004e+07 9.42102e+06 1.23546e+07 1.11620e+07 8.45101e+06 1.26371e+07 −1.05127e+07 9.12845e+06 2.07304e+07 1.24363e+07 −1.36434e+06 9.45781e+06 4.30220e+06 8.83182e+06 −1.00980e+06 4.41410e+06 1.18688e+08 7.52622e+07 8457.33 5561.57 −1.94844e+06 4.92357e+06 5.72514e+06 3.96344e+06 −485526. 1.55123e+06 −40312.1 499384. −1.57673e+07 1.14850e+07

t-ratio

p-value

−1.200 −0.7072 0.04057 0.4186 −0.5907 −2.062 2.611 1.107 0.6687 −1.152 1.667 −0.1443 0.4871 −0.2288 1.577 1.521 −0.3957 1.444 −0.3130 −0.08072 −1.373

0.2337 0.4816 0.9677 0.6767 0.5565 0.0426 0.0109 0.2719 0.5057 0.2531 0.0996 0.8857 0.6276 0.8197 0.1190 0.1325 0.6934 0.1527 0.7551 0.9359 0.1738

Unadjusted R-squared = 0.382442 Test statistic: T R2 = 37.096919, with p-value = P (Chi-square(20) > 37.096919) = 0.011393 Tabulka B.6: Whiteův test pro pronájem bytů

lv



Coefficient

Std. error

t-ratio

p-value

−3.86172 0.0589666 −0.959470 0.816236 −1.53068 −1.70066 3.24940 2.18362 1.20856 −1.65671 2.67097 −0.129838 0.428380 −0.156445 1.75548

5.37681 0.0303083 0.802733 1.38009 1.65439 0.521282 1.09524 1.28827 1.45883 1.03693 1.45243 1.08622 0.327498 0.220780 0.858492

−0.7182 1.946 −1.195 0.5914 −0.9252 −3.262 2.967 1.695 0.8284 −1.598 1.839 −0.1195 1.308 −0.7086 2.045

0.4747 0.0551 0.2354 0.5559 0.3576 0.0016 0.0039 0.0939 0.4098 0.1140 0.0695 0.9051 0.1945 0.4806 0.0441

Explained sum of squares = 637.789 Test statistic: LM = 318.894644, with p-value = P (Chi-square(14) > 318.894644) = 0.000000 Tabulka B.7: Breusch-Paganův test pro pronájem bytů

lvi


Coefficient const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Std. Error

−4445.76 1978.15 23.6140 12.4366 2066.87 334.934 1167.72 416.489 433.750 496.740 −583.356 207.783 953.559 420.328 832.797 510.941 1881.05 409.613 −218.163 379.492 2629.15 386.013 388.270 345.118 320.837 100.586 143.220 86.8019 1345.51 350.678

t-ratio

p-value

−2.2474 1.8987 6.1710 2.8037 0.8732 −2.8075 2.2686 1.6299 4.5923 −0.5749 6.8110 1.1250 3.1897 1.6500 3.8369

0.0273 0.0611 0.0000 0.0063 0.3851 0.0062 0.0259 0.1070 0.0000 0.5669 0.0000 0.2639 0.0020 0.1028 0.0002

Statistics based on the weighted data: Sum squared resid 158491.6 S.E. of regression R2 0.966967 Adjusted R2 F (14, 82) 171.4549 P-value(F ) Log-likelihood −496.4762 Akaike criterion Schwarz criterion 1061.573 Hannan–Quinn Statistics based on the original data: Mean dependent var 10367.11 S.D. dependent var Sum squared resid 8.60e+08 S.E. of regression

43.96390 0.961327 1.67e–54 1022.952 1038.569 4714.400 3239.380

Tabulka B.8: Odhad metodou WLS pro pronájem bytů

lvii


const Pokoj Vlastnictvi Stav Balkon Lodzie Garaz Vybaveni MHD

Coefficient

Std. Error

t-ratio

p-value

−2511.32 2896.44 1317.88 −510.735 749.050 1816.25 2300.82 432.752 956.719

1517.06 134.865 417.763 150.001 283.419 442.912 509.070 82.3677 228.747

−1.6554 21.4766 3.1546 −3.4049 2.6429 4.1007 4.5197 5.2539 4.1824

0.1014 0.0000 0.0022 0.0010 0.0097 0.0001 0.0000 0.0000 0.0001

Statistics based on the weighted data: Sum squared resid 160069.2 S.E. of regression R2 0.934586 Adjusted R2 F (8, 88) 157.1590 P-value(F ) Log-likelihood −496.9566 Akaike criterion Schwarz criterion 1035.086 Hannan–Quinn Statistics based on the original data: Mean dependent var 10367.11 S.D. dependent var Sum squared resid 9.46e+08 S.E. of regression

42.64936 0.928639 1.03e–48 1011.913 1021.283 4714.400 3277.942

Tabulka B.9: Odhad metodou WLS pro pronájem bytů, zúžený model

lviii

PŘÍLOHA C. INSTRUMENTÁLNÍ PROMĚNNÉ PRODEJ BYTŮ

Příloha C Instrumentální proměnné Prodej bytů

lix


const Pokoj Balkon Terasa Lodzie Sklep

Coefficient

Std. Error

19.5547 23.2431 5.97209 20.2691 −4.31710 −5.12603

2.05470 0.821742 1.66068 1.78076 2.50783 1.58439


73.77701 47634.59 0.824079 292.3056 −1247.695 2529.963

t-ratio

p-value

9.5171 28.2852 3.5962 11.3823 −1.7214 −3.2353

0.0000 0.0000 0.0004 0.0000 0.0862 0.0013


Tabulka C.1: Odhad metodou OLS pro Podlahovou plochu bytu pro prodej bytů

lx


const m2 Vlastnictvi Zdivo Stav Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-stat

p-value

−2.11732e+006 24263.1 606345. 126697. 63355.7 103214. −10130.3 165040. 109096. −47032.3

379111. 1431.55 111266. 128408. 59234.8 175785. 141895. 38401.0 21787.2 55064.0

−5.5850 16.9488 5.4495 0.9867 1.0696 0.5872 −0.0714 4.2978 5.0073 −0.8541

0.0000 0.0000 0.0000 0.3238 0.2848 0.5571 0.9431 0.0000 0.0000 0.3930

Mean dependent var Sum squared resid R2 F (9, 308)

2349384 1.17e+14 0.654617 56.22855

S.D. dependent var 1034754 S.E. of regression 617065.9 2 Adjusted R 0.644525 P-value(F ) 7.80e–60

Hausman test – Null hypothesis: OLS estimates are consistent Asymptotic test statistic: χ2 (1) = 1.02308 with p-value = 0.311789 Sargan over-identification test – Null hypothesis: all instruments are valid Test statistic: LM = 64.0841 with p-value = P (χ2 (4) > 64.0841) = 4.01215e-013 Weak instrument test – First-stage F (5, 304) = 289.373 Tabulka C.2: Odhad metodou 2SLS pro prodej bytů

lxi


const m2 Vlastnictvi Zdivo Stav Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-stat

p-value

−2.11733e+006 24072.1 605171. 130276. 64798.4 108430. −8734.20 164248. 109354. −45217.2

379206. 1471.45 111313. 128597. 59304.9 176073. 141953. 38436.4 21797.5 55171.8

−5.5836 16.3594 5.4367 1.0131 1.0926 0.6158 −0.0615 4.2732 5.0168 −0.8196

0.0000 0.0000 0.0000 0.3110 0.2746 0.5380 0.9509 0.0000 0.0000 0.4125

Mean dependent var Sum squared resid Log-likelihood Schwarz criterion

2349384 1.17e+14 −7123.330 14304.28

S.D. dependent var S.E. of regression Akaike criterion Hannan–Quinn

1034754 617221.4 14266.66 14281.69

Smallest eigenvalue = 1.25231 LR over-identification test: χ2 (4) = 71.548 [0.0000] Weak instrument test – First-stage F (5, 304) = 289.373 Tabulka C.3: Odhad metodou LIML pro prodej bytů

lxii

PŘÍLOHA D. INSTRUMENTÁLNÍ PROMĚNNÉ PRONÁJEM BYTŮ

Příloha D Instrumentální proměnné Pronájem bytů

lxiii


const Pokoj Balkon Terasa Lodzie Sklep

Coefficient

Std. Error

20.9066 21.6089 −2.55600 21.4916 0.192574 −0.849753

3.74311 1.82367 4.32302 4.73496 5.75032 3.85123


61.33247 24814.14 0.715324 45.73227 −406.5432 840.5348

t-ratio

p-value

5.5854 11.8491 −0.5913 4.5389 0.0335 −0.2206

0.0000 0.0000 0.5558 0.0000 0.9734 0.8259


Tabulka D.1: Odhad metodou OLS pro Podlahovou plochu bytu pro pronájem bytů

lxiv


const Pokoj Terasa

Coefficient

Std. Error

t-ratio

20.1808 21.4520 22.1026

3.32112 1.76545 4.38962

6.0765 0.0000 12.1510 0.0000 5.0352 0.0000


61.33247 24963.71 0.713608 117.1106 −406.8347 827.3935

p-value


Tabulka D.2: Odhad metodou OLS pro Podlahovou plochu bytů pro pronájem bytů, zúžený model

lxv


const m2 Vlastnictvi Zdivo Stav Balkon Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-stat

p-value

−9549.79 128.134 1444.48 −995.611 −1183.77 2333.20 2041.04 −686.497 1421.64 661.647 497.341 19.6607 2945.90

4603.40 16.4334 1153.31 1375.72 415.534 861.277 1223.57 850.005 1218.86 903.569 269.852 183.786 707.145

−2.0745 7.7972 1.2525 −0.7237 −2.8488 2.7090 1.6681 −0.8076 1.1664 0.7323 1.8430 0.1070 4.1659

0.0380 0.0000 0.2104 0.4692 0.0044 0.0067 0.0953 0.4193 0.2435 0.4640 0.0653 0.9148 0.0000

Mean dependent var Sum squared resid R2 F (12, 84)

10367.11 9.26e+08 0.575284 9.686454

S.D. dependent var 4714.400 S.E. of regression 3320.676 2 Adjusted R 0.514610 P-value(F ) 1.57e–11

Hausman test – Null hypothesis: OLS estimates are consistent Asymptotic test statistic: χ2 (1) = 9.4168 with p-value = 0.00215006 Sargan over-identification test – Null hypothesis: all instruments are valid Test statistic: LM = 0.585702 with p-value = P (χ2 (1) > 0.585702) = 0.444086 Weak instrument test – First-stage F (2, 83) = 99.4970 Tabulka D.3: Odhad metodou 2SLS pro pronájem bytů

lxvi


const m2 Vlastnictvi Zdivo Stav Balkon Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-stat

p-value

−9570.86 128.340 1445.00 −999.721 −1182.90 2335.30 2042.93 −686.314 1415.86 660.770 496.726 19.5150 2949.76

4605.60 16.4593 1153.66 1376.24 415.677 861.584 1223.98 850.267 1219.46 903.854 269.947 183.844 707.533

−2.0781 7.7974 1.2525 −0.7264 −2.8457 2.7105 1.6691 −0.8072 1.1611 0.7311 1.8401 0.1061 4.1691

0.0377 0.0000 0.2104 0.4676 0.0044 0.0067 0.0951 0.4196 0.2456 0.4647 0.0658 0.9155 0.0000

Mean dependent var Sum squared resid Log-likelihood Schwarz criterion

10367.11 9.27e+08 −1556.733 3172.938

S.D. dependent var S.E. of regression Akaike criterion Hannan–Quinn

4714.400 3321.700 3139.466 3153.001

Smallest eigenvalue = 1.00607 LR over-identification test: χ2 (1) = 0.587296 [0.4435] Weak instrument test – First-stage F (2, 83) = 99.4970 Tabulka D.4: Odhad metodou LIML pro pronájem bytů

lxvii


lxviii

PŘÍLOHA E. MODELY BINÁRNÍ VOLBY PRODEJ BYTŮ

Příloha E Modely binární volby Prodej bytů

lxix


const m2 Pokoj Vlastnictvi Zdivo Stav Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

−0.0343679 0.00418411 −0.0109177 0.124047 −0.158287 0.107946 −0.377587 −0.643939 −0.0400093 0.0310607 0.0668719 −0.0579811 −0.0412763 0.108890

0.280422 0.00199571 0.0560719 0.0726285 0.0887837 0.0391437 0.0677780 0.0784993 0.0567070 0.115825 0.0923570 0.0252859 0.0141182 0.0375681

−0.1226 2.0966 −0.1947 1.7080 −1.7828 2.7577 −5.5709 −8.2031 −0.7055 0.2682 0.7241 −2.2930 −2.9236 2.8985

0.9025 0.0369 0.8458 0.0887 0.0756 0.0062 0.0000 0.0000 0.4810 0.7887 0.4696 0.0225 0.0037 0.0040


0.635220 47.95078 0.349251 12.55031 −150.4141 381.4970

S.D. dependent var 0.482127 S.E. of regression 0.397156 2 Adjusted R 0.321423 P-value(F ) 5.59e–22 Akaike criterion 328.8282 Hannan–Quinn 349.8645

White’s test for heteroskedasticity – Null hypothesis: heteroskedasticity not present Test statistic: LM = 229.672 with p-value = P (χ2 (96) > 229.672) = 5.79138e-013 Tabulka E.1: Odhad metodou OLS pro Balkon pro prodej bytů

lxx


const m2 Stav Terasa Lodzie Vybaveni Patro MHD

Coefficient

Std. Error

t-stat

p-value

−2.80677 0.0221928 0.585365 −2.09773 −4.43434 −0.363777 −0.232828 0.637441

1.11634 0.00627349 0.198818 0.407709 0.855996 0.155588 0.0927264 0.235624

−2.5143 3.5376 2.9442 −5.1452 −5.1803 −2.3381 −2.5109 2.7053

0.0119 0.0004 0.0032 0.0000 0.0000 0.0194 0.0120 0.0068

Mean dependent var McFadden R2 Log-likelihood Schwarz criterion

0.635220 0.293059 −147.5002 341.0967

S.D. dependent var 0.234506 Adjusted R2 0.254717 Akaike criterion 311.0003 Hannan–Quinn 323.0210

Number of cases ‘correctly predicted’ = 253 (79.6 percent) Likelihood ratio test: χ2 (7) = 122.291 [0.0000] Tabulka E.2: Logit model pro Balkon pro prodej bytů

lxxi


const m2 Stav Terasa Lodzie Vybaveni Patro MHD

Coefficient

Std. Error

t-stat

p-value

−1.57780 0.0132116 0.339577 −1.21662 −2.50397 −0.188700 −0.135097 0.341232

0.636060 0.00357606 0.111839 0.238178 0.418592 0.0869006 0.0520131 0.133268

−2.4806 3.6945 3.0363 −5.1080 −5.9819 −2.1714 −2.5974 2.5605

0.0131 0.0002 0.0024 0.0000 0.0000 0.0299 0.0094 0.0105


0.635220 0.292442 −147.6289 341.3542


Number of cases ‘correctly predicted’ = 248 (78.0 percent) Likelihood ratio test: χ2 (7) = 122.034 [0.0000] Tabulka E.3: Probit model pro Balkon pro prodej bytů

lxxii


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

−0.713945 0.0117893 −0.130073 0.0645097 −0.0587285 0.0675799 −0.245329 −0.206910 −0.186377 −0.0597637 0.163143 −0.00672742 −0.0203990 0.117776

0.222302 0.00147241 0.0445801 0.0587065 0.0718590 0.0317083 0.0440373 0.0689139 0.0444801 0.0933093 0.0739194 0.0205537 0.0114795 0.0299452

−3.2116 8.0068 −2.9177 1.0989 −0.8173 2.1313 −5.5709 −3.0024 −4.1901 −0.6405 2.2070 −0.3273 −1.7770 3.9330

0.0015 0.0000 0.0038 0.2727 0.4144 0.0339 0.0000 0.0029 0.0000 0.5223 0.0281 0.7437 0.0766 0.0001


0.308176 31.15497 0.540479 27.50445 −81.85313 244.3750


Tabulka E.4: Odhad metodou OLS pro Terasa pro prodej bytů

lxxiii


const m2 Pokoj Stav Balkon Lodzie Sklep Parking MHD

Coefficient

Std. Error

t-stat

p-value

−26.1525 0.133887 −1.72293 3.95551 −2.59838 −5.69717 −2.10366 3.86457 1.52834

4.99243 0.0248116 0.657648 0.998962 0.511329 1.58149 0.578471 1.35226 0.377607

−5.2384 5.3961 −2.6198 3.9596 −5.0816 −3.6024 −3.6366 2.8579 4.0474

0.0000 0.0000 0.0088 0.0001 0.0000 0.0003 0.0003 0.0043 0.0001


0.308176 0.632657 −72.14891 196.1563


Number of cases ‘correctly predicted’ = 267 (84.0 percent) Likelihood ratio test: χ2 (8) = 248.517 [0.0000] Tabulka E.5: Logit model pro Terasu pro prodej bytů

lxxiv


const m2 Pokoj Stav Balkon Lodzie Sklep Parking MHD

Coefficient

Std. Error

t-stat

p-value

−14.2776 0.0765102 −1.06423 2.17705 −1.56170 −3.14383 −1.09374 2.18124 0.817139

2.59221 0.0133320 0.369219 0.547445 0.288451 0.860313 0.301692 0.766315 0.190317

−5.5079 5.7388 −2.8824 3.9768 −5.4141 −3.6543 −3.6254 2.8464 4.2936

0.0000 0.0000 0.0039 0.0001 0.0000 0.0003 0.0003 0.0044 0.0000


0.308176 0.636173 −71.45825 194.7750


Number of cases ‘correctly predicted’ = 267 (84.0 percent) Likelihood ratio test: χ2 (8) = 249.898 [0.0000] Tabulka E.6: Probit model pro Terasu pro prodej bytů

lxxv


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

0.844953 −5.88467e–006 0.0560013 −0.0503244 −0.329112 0.0367105 −0.281448 −0.139188 0.0473658 0.0595276 −0.0636317 −0.0173911 −0.0107235 0.0181491

0.178950 0.00132890 0.0369329 0.0481592 0.0559014 0.0261154 0.0343099 0.0463584 0.0374220 0.0765062 0.0610022 0.0168313 0.00944407 0.0251562

4.7217 −0.0044 1.5163 −1.0450 −5.8874 1.4057 −8.2031 −3.0024 1.2657 0.7781 −1.0431 −1.0333 −1.1355 0.7215

0.0000 0.9965 0.1305 0.2969 0.0000 0.1608 0.0000 0.0029 0.2066 0.4371 0.2977 0.3023 0.2571 0.4712


0.128931 20.95798 0.413169 16.46438 −18.81687 118.3025


Tabulka E.7: Odhad metodou OLS pro Lodžie pro prodej bytů

lxxvi


const Zdivo Balkon Terasa

Coefficient

Std. Error

2.84384 −1.85241 −3.90044 −2.73052

0.803095 0.477270 0.758219 1.05870


0.128931 0.490831 −62.23216 147.5125

t-stat

p-value

3.5411 −3.8813 −5.1442 −2.5791

0.0004 0.0001 0.0000 0.0099


Number of cases ‘correctly predicted’ = 292 (91.8 percent) Likelihood ratio test: χ2 (3) = 119.982 [0.0000] Tabulka E.8: Logit model pro Lodžii pro prodej bytů

const Zdivo Balkon Terasa

Coefficient

Std. Error

1.63455 −1.06901 −2.00361 −1.41313

0.453770 0.269175 0.332752 0.465396


0.128931 0.490153 −62.31509 147.6784

t-stat

p-value

3.6022 −3.9714 −6.0213 −3.0364

0.0003 0.0001 0.0000 0.0024


Number of cases ‘correctly predicted’ = 292 (91.8 percent) Likelihood ratio test: χ2 (3) = 119.816 [0.0000] Tabulka E.9: Probit model pro Lodžii pro prodej bytů

lxxvii


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

−0.338761 −0.00769308 0.278353 −0.0300100 0.157383 −0.0519193 −0.0408605 −0.292957 0.110676 0.190738 0.0945431 0.0939896 −0.00967300 0.179088

0.282730 0.00198285 0.0543735 0.0737282 0.0897381 0.0399388 0.0579134 0.0699159 0.0874412 0.116552 0.0932572 0.0252034 0.0144562 0.0370907

−1.1982 −3.8798 5.1193 −0.4070 1.7538 −1.3000 −0.7055 −4.1901 1.2657 1.6365 1.0138 3.7292 −0.6691 4.8284

0.2318 0.0001 0.0000 0.6843 0.0805 0.1946 0.4810 0.0000 0.2066 0.1028 0.3115 0.0002 0.5039 0.0000


0.383648 48.97089 0.348748 12.52254 −153.7612 388.1912


Tabulka E.10: Odhad metodou OLS pro Sklep pro prodej bytů

lxxviii


const m2 Pokoj Terasa Vybaveni MHD

Coefficient

Std. Error

t-stat

p-value

−4.98928 −0.0505651 1.82888 −1.74487 0.501639 1.09369

0.985355 0.0120519 0.324197 0.460577 0.151765 0.257747

−5.0634 −4.1956 5.6413 −3.7885 3.3054 4.2433

0.0000 0.0000 0.0000 0.0002 0.0009 0.0000


0.383648 0.281570 −152.1141 338.8005


Number of cases ‘correctly predicted’ = 250 (78.6 percent) Likelihood ratio test: χ2 (5) = 119.234 [0.0000] Tabulka E.11: Logit model pro Sklep pro prodej bytů

const m2 Pokoj Terasa Vybaveni MHD

Coefficient

Std. Error

−2.76576 −0.0299222 1.08152 −0.995875 0.299139 0.589293

0.513470 −5.3864 0.0000 0.00672448 −4.4497 0.0000 0.182778 5.9171 0.0000 0.251718 −3.9563 0.0001 0.0815447 3.6684 0.0002 0.132032 4.4633 0.0000


0.383648 0.280359 −152.3705 339.3133

t-stat

p-value


Number of cases ‘correctly predicted’ = 251 (78.9 percent) Likelihood ratio test: χ2 (5) = 118.722 [0.0000] Tabulka E.12: Probit model pro Sklep pro prodej bytů

lxxix


lxxx

Příloha F Modely binární volby Pronájem bytů

PŘÍLOHA F. MODELY BINÁRNÍ VOLBY PRONÁJEM BYTŮ

const m2 Pokoj Vlastnictvi Zdivo Stav Terasa Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

0.493988 −0.00540444 0.158071 −0.0682248 0.247051 0.0121510 −0.315111 −0.290376 0.249511 0.259876 0.0865603 −0.0274504 0.0279383 −0.137175

0.536126 0.00297899 0.0785561 0.138109 0.163570 0.0522256 0.124390 0.142687 0.100246 0.142739 0.108445 0.0326830 0.0219129 0.0847098

0.9214 −1.8142 2.0122 −0.4940 1.5104 0.2327 −2.5332 −2.0351 2.4890 1.8206 0.7982 −0.8399 1.2750 −1.6194

0.3595 0.0733 0.0474 0.6226 0.1347 0.8166 0.0132 0.0450 0.0148 0.0723 0.4270 0.4034 0.2059 0.1092


0.247423 13.04200 0.277926 2.457430 −40.32006 144.6861

S.D. dependent var 0.433756 S.E. of regression 0.396400 Adjusted R2 0.164830 P-value(F ) 0.007115 Akaike criterion 108.6401 Hannan–Quinn 123.2153

Tabulka F.1: Odhad metodou OLS pro Balkon pro pronájem bytů

lxxxii


const Pokoj Terasa Sklep

Coefficient

Std. Error

−1.88439 0.408337 −2.87285 1.63558

0.627879 0.295073 1.15668 0.571482


0.275862 0.166814 −42.69515 103.2539

t-stat

p-value

−3.0012 1.3838 −2.4837 2.8620

0.0027 0.1664 0.0130 0.0042


Number of cases ‘correctly predicted’ = 68 (78.2 percent) Likelihood ratio test: χ2 (3) = 17.096 [0.0007] Tabulka F.2: Logit model pro Balkon pro pronájem bytů

const Pokoj Terasa Sklep

Coefficient

Std. Error

−1.14239 0.257156 −1.56661 0.949327

0.351987 0.169263 0.573287 0.337451


0.275862 0.163517 −42.86406 103.5918

t-stat

p-value

−3.2455 1.5193 −2.7327 2.8132

0.0012 0.1287 0.0063 0.0049


Number of cases ‘correctly predicted’ = 68 (78.2 percent) Likelihood ratio test: χ2 (3) = 16.758 [0.0008] Tabulka F.3: Probit model pro Balkon pro pronájem bytů

lxxxiii


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Lodzie Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

0.0437342 0.00709231 −0.0677038 −0.0998666 0.157229 −0.0210511 −0.227755 −0.0890918 0.166873 0.0777820 0.0551802 0.0208377 −0.0143308 −0.0385745

0.458094 0.00246222 0.0679901 0.117076 0.139898 0.0443545 0.0899065 0.123911 0.0864293 0.123456 0.0923504 0.0278098 0.0187452 0.0730233

0.0955 2.8805 −0.9958 −0.8530 1.1239 −0.4746 −2.5332 −0.7190 1.9307 0.6300 0.5975 0.7493 −0.7645 −0.5282

0.9242 0.0051 0.3222 0.3961 0.2643 0.6363 0.0132 0.4742 0.0569 0.5304 0.5518 0.4558 0.4467 0.5987


0.195876 9.426455 0.383019 3.963536 −24.57428 113.1945

S.D. dependent var 0.398935 S.E. of regression 0.337004 Adjusted R2 0.286383 P-value(F ) 0.000052 Akaike criterion 77.14856 Hannan–Quinn 91.72378

Tabulka F.4: Odhad metodou OLS pro Terasu pro pronájem bytů

lxxxiv


Coefficient const m2 Balkon

Std. Error

−4.37078 0.909263 0.0471435 0.0117683 −2.36952 1.21860


0.195876 0.314795 −32.87568 79.47550

t-stat

p-value

−4.8069 0.0000 4.0060 0.0001 −1.9445 0.0518


Number of cases ‘correctly predicted’ = 81 (83.5 percent) Likelihood ratio test: χ2 (2) = 30.207 [0.0000] Tabulka F.5: Logit model pro Terasu pro pronájem bytů

Coefficient const m2 Balkon

Std. Error

t-stat

p-value

−2.47274 0.462119 −5.3509 0.0000 0.0265688 0.00624903 4.2517 0.0000 −1.39788 0.681550 −2.0510 0.0403


0.195876 0.315902 −32.82256 79.36924


Number of cases ‘correctly predicted’ = 81 (83.5 percent) Likelihood ratio test: χ2 (2) = 30.314 [0.0000] Tabulka F.6: Probit model pro Terasu pro pronájem bytů

lxxxv


const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Sklep Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

0.550219 −0.000433717 −0.0128251 −0.0570731 −0.185782 0.0563591 −0.163670 −0.0694773 0.00355363 0.0427988 −0.0198012 0.0165147 0.0156741 −0.0267482

0.400025 0.00227994 0.0603823 0.103651 0.122797 0.0387310 0.0804252 0.0966307 0.0780186 0.109181 0.0816995 0.0245746 0.0165225 0.0645273

1.3755 −0.1902 −0.2124 −0.5506 −1.5129 1.4551 −2.0351 −0.7190 0.0455 0.3920 −0.2424 0.6720 0.9487 −0.4145

0.1727 0.8496 0.8323 0.5834 0.1341 0.1494 0.0450 0.4742 0.9638 0.6961 0.8091 0.5034 0.3456 0.6796


0.103093 7.351119 0.180392 1.405229 −12.51390 89.07376

S.D. dependent var 0.305660 S.E. of regression 0.297603 2 Adjusted R 0.052020 P-value(F ) 0.174470 Akaike criterion 53.02781 Hannan–Quinn 67.60303

Tabulka F.7: Odhad metodou OLS pro Lodžii pro pronájem bytů

const

Coefficient

Std. Error

−1.84055

0.340401


0.136986 0.000000 −29.16020 62.61086

t-stat

p-value

−5.4070 0.0000

S.D. dependent var 0.118221 2 Adjusted R −0.034293 Akaike criterion 60.32040 Hannan–Quinn 61.23319

Number of cases ‘correctly predicted’ = 63 (86.3 percent) Tabulka F.8: Logit model pro Lodžii pro pronájem bytů

lxxxvi


const

Coefficient

Std. Error

−1.09396

0.183504

Mean dependent var Log-likelihood Schwarz criterion

t-stat

p-value

−5.9615 0.0000

0.136986 S.D. dependent var −29.16020 Akaike criterion 62.61086 Hannan–Quinn

0.219300 60.32040 61.23319

Number of cases ‘correctly predicted’ = 63 (86.3 percent) Tabulka F.9: Probit model pro Lodžii pro pronájem bytů

const m2 Pokoj Vlastnictvi Zdivo Stav Balkon Terasa Lodzie Garaz Parking Vybaveni Patro MHD

Coefficient

Std. Error

t-ratio

p-value

1.70897 −0.000649126 −0.0296234 −0.00375096 −0.596344 0.0453462 0.278364 0.257576 0.00703375 0.129412 0.0184849 0.0197929 −0.0154974 −0.131639

0.537365 0.00320751 0.0849115 0.146090 0.162434 0.0549556 0.111839 0.133408 0.154423 0.153090 0.114964 0.0345993 0.0233088 0.0897201

3.1803 −0.2024 −0.3489 −0.0257 −3.6713 0.8251 2.4890 1.9307 0.0455 0.8453 0.1608 0.5721 −0.6649 −1.4672

0.0021 0.8401 0.7281 0.9796 0.0004 0.4117 0.0148 0.0569 0.9638 0.4004 0.8727 0.5688 0.5080 0.1461


0.309278 14.55016 0.297828 2.708051 −45.62726 155.3005

S.D. dependent var 0.464597 S.E. of regression 0.418692 2 Adjusted R 0.187849 P-value(F ) 0.003145 Akaike criterion 119.2545 Hannan–Quinn 133.8297

Tabulka F.10: Odhad metodou OLS pro Sklep pro pronájem bytů

lxxxvii


const Zdivo Balkon

Coefficient

Std. Error

2.78074 −2.14233 1.21062

1.23872 0.666550 0.526731


0.309278 0.140610 −51.56050 116.8451

t-stat

p-value

2.2448 0.0248 −3.2141 0.0013 2.2984 0.0215


Number of cases ‘correctly predicted’ = 73 (75.3 percent) Likelihood ratio test: χ2 (2) = 16.872 [0.0002] Tabulka F.11: Logit model pro Sklep pro pronájem bytů

const Zdivo Balkon

Coefficient

Std. Error

1.72489 −1.31645 0.731137

0.750827 0.400012 0.317735


0.309278 0.141015 −51.53624 116.7966

t-stat

p-value

2.2973 0.0216 −3.2910 0.0010 2.3011 0.0214


Number of cases ‘correctly predicted’ = 73 (75.3 percent) Likelihood ratio test: χ2 (2) = 16.921 [0.0002] Tabulka F.12: Probit model pro Sklep pro pronájem bytů

lxxxviii

OBSAH

Obsah A Metoda nejmenších čtverců Prodej bytů

i

B Metoda nejmenších čtverců Pronájem bytů

xxxi

C Instrumentální proměnné Prodej bytů

lix

D Instrumentální proměnné Pronájem bytů

lxiii

E Modely binární volby Prodej bytů

lxix

F Modely binární volby Pronájem bytů

lxxxi

Seznam tabulek

xcii

lxxxix

OBSAH

xc

SEZNAM TABULEK

Seznam tabulek A.1 Kontingenční tabulky pro prodej bytů . . . . . . . . . . . . . . . . . . . . . xx A.2 Korelační matice pro prodej bytů . . . . . . . . . . . . . . . . . . . . . . . xxi A.3 Odhad metodou OLS pro prodej bytů . . . . . . . . . . . . . . . . . . . . . xxii A.4 RESET test pro prodej bytů . . . . . . . . . . . . . . . . . . . . . . . . . . xxiii A.5 Test multikolinearity pro prodej bytů . . . . . . . . . . . . . . . . . . . . . xxiv A.6 Whiteův test pro prodej bytů . . . . . . . . . . . . . . . . . . . . . . . . . xxviii A.7 Breusch-Paganův test pro prodej bytů

. . . . . . . . . . . . . . . . . . . . xxviii

A.8 Odhad metodou WLS pro prodej bytů . . . . . . . . . . . . . . . . . . . . xxix A.9 Odhad metodou WLS pro prodej bytů, zúžený model . . . . . . . . . . . . xxx B.1 Kontingenční tabulky pro pronájem bytů . . . . . . . . . . . . . . . . . . .

l

B.2 Korelační matice pro pronájem bytů . . . . . . . . . . . . . . . . . . . . .

li

B.3 Odhad metodou OLS pro pronájem bytů . . . . . . . . . . . . . . . . . . .

lii

B.4 RESET test pro pronájem bytů . . . . . . . . . . . . . . . . . . . . . . . . liii B.5 Test multikolinearity pro pronájem bytů . . . . . . . . . . . . . . . . . . . liv B.6 Whiteův test pro pronájem bytů . . . . . . . . . . . . . . . . . . . . . . . .

lv

B.7 Breusch-Paganův test pro pronájem bytů . . . . . . . . . . . . . . . . . . . lvi B.8 Odhad metodou WLS pro pronájem bytů . . . . . . . . . . . . . . . . . . . lvii B.9 Odhad metodou WLS pro pronájem bytů, zúžený model . . . . . . . . . . lviii C.1 Odhad metodou OLS pro Podlahovou plochu bytu pro prodej bytů

. . . .

lx

C.2 Odhad metodou 2SLS pro prodej bytů . . . . . . . . . . . . . . . . . . . . lxi C.3 Odhad metodou LIML pro prodej bytů . . . . . . . . . . . . . . . . . . . . lxii D.1 Odhad metodou OLS pro Podlahovou plochu bytu pro pronájem bytů . . . lxiv D.2 Odhad metodou OLS pro Podlahovou plochu bytů pro pronájem bytů, zúžený model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . lxv D.3 Odhad metodou 2SLS pro pronájem bytů . . . . . . . . . . . . . . . . . . . lxvi D.4 Odhad metodou LIML pro pronájem bytů . . . . . . . . . . . . . . . . . . lxvii xci

SEZNAM TABULEK E.1 E.2 E.3 E.4 E.5 E.6 E.7 E.8 E.9 E.10 E.11 E.12

Odhad metodou OLS pro Balkon pro prodej bytů Logit model pro Balkon pro prodej bytů . . . . . Probit model pro Balkon pro prodej bytů . . . . . Odhad metodou OLS pro Terasa pro prodej bytů Logit model pro Terasu pro prodej bytů . . . . . Probit model pro Terasu pro prodej bytů . . . . . Odhad metodou OLS pro Lodžie pro prodej bytů Logit model pro Lodžii pro prodej bytů . . . . . . Probit model pro Lodžii pro prodej bytů . . . . . Odhad metodou OLS pro Sklep pro prodej bytů . Logit model pro Sklep pro prodej bytů . . . . . . Probit model pro Sklep pro prodej bytů . . . . . .

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lxx lxxi lxxii lxxiii lxxiv lxxv lxxvi lxxvii lxxvii lxxviii lxxix lxxix

F.1 F.2 F.3 F.4 F.5 F.6 F.7 F.8 F.9 F.10 F.11 F.12

Odhad metodou OLS pro Balkon pro pronájem bytů Logit model pro Balkon pro pronájem bytů . . . . . . Probit model pro Balkon pro pronájem bytů . . . . . Odhad metodou OLS pro Terasu pro pronájem bytů . Logit model pro Terasu pro pronájem bytů . . . . . . Probit model pro Terasu pro pronájem bytů . . . . . Odhad metodou OLS pro Lodžii pro pronájem bytů . Logit model pro Lodžii pro pronájem bytů . . . . . . Probit model pro Lodžii pro pronájem bytů . . . . . Odhad metodou OLS pro Sklep pro pronájem bytů . Logit model pro Sklep pro pronájem bytů . . . . . . Probit model pro Sklep pro pronájem bytů . . . . . .

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lxxxii lxxxiii lxxxiii lxxxiv lxxxv lxxxv lxxxvi lxxxvi lxxxvii lxxxvii lxxxviii lxxxviii

xcii

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PŘÍLOHA A. METODA NEJMENŠÍCH ČTVERCŮ PRODEJ BYTŮ. Příloha A. Metoda nejmenších čtverců Prodej bytů

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