1# RECORD ede799d5a89d38a16239a4734a2cb00510a8c5012# TITLE: The COVID-19 Pandemic, Airbnb and Housing Market Dynamics in Warsaw3# YEAR: 2021.0 VENUE: Critical Housing Analysis DOI: 10.13060/23362839.2021.8.1.5244# AUTHORS: R. Trojanek; Michał Głuszak; Michał Hebdzyński; Justyna Tanas5# PAGES: 13 CANDIDATE TABLE PAGES (1-based): [7, 10]6# ABSTRACT: In this study, we analyse the impact of COVID-19 on house rents and prices in Warsaw, the capital of Poland. Hedonic indexes indicate a slight increase in prices (ca. 1.2%) and a substantial drop in long-term rents (ca. -7.7%) between March 2020 and December 2020. The largest decline in rents occurred in centrally located neighbourhoods, which was largely due to the inflow of new housing supply from the short-term rental market (the Airbnb Warsaw market shrank by almost 30% in December 2020 y/y). Using hedonic methods, we show the effect of the shrinking Airbnb market on the drop in long-term rents. The study indicates the elasticity of rents with respect to Airbnb supply, with a 1% change in Airbnb listings leading to a 0.031% change in rents.789===== PAGE 1 (score 2, numeric-paren 0, table-words 0, var-words 2) =====1011Volume 8 | Issue 1 | 2021 | 72-84 12Available online at www.housing-critical.com 13https://dx.doi.org/10.13060/23362839.2021.8.1.524 14 1572 16 17The COVID-19 Pandemic, Airbnb and Housing Market 18Dynamics in Warsaw 19 20Radoslaw Trojanek (corresponding author) 21 22Poznań Univeristy of Economics and Business, Poland 23radoslaw.trojanek@ue.poznan.pl 24 25 26Michal Gluszak 27 28Cracow University of Economics, Poland 29gluszakm@uek.krakow.pl 30 31 32Michal Hebdzynski 33 34Poznań Univeristy of Economics and Business, Poland 35michal.hebdzynski@phd.ue.poznan.pl 36 37 38Justyna Tanas 39 40WSB University in Poznan, Poland 41justyna.tanas@wsb.poznan.pl 42 43 44Abstract: In this study, we analyse the impact of COVID-19 on house rents and prices in Warsaw, the capital of 45Poland. Hedonic indexes indicate a slight increase in prices (ca. 1.2%) and a substantial drop in long-term rents 46(ca. -7.7%) between March 2020 and December 2020. The largest decline in rents occurred in centrally located 47neighbourhoods, which was largely due to the inflow of new housing supply from the short-term rental market (the 48Airbnb Warsaw market shrank by almost 30% in December 2020 y/y). Using hedonic methods, we show the effect 49of the shrinking Airbnb market on the drop in long-term rents. The study indicates the elasticity of rents with 50respect to Airbnb supply, with a 1% change in Airbnb listings leading to a 0.031% change in rents. 51 52Keywords: housing market; Airbnb; COVID-19. 53 54 55 56 57 58 59 606162===== PAGE 7 (score 20, numeric-paren 12, table-words 2, var-words 1) =====6364Volume 8 | Issue 1 | 2021 | 72-84 65Available online at www.housing-critical.com 66https://dx.doi.org/10.13060/23362839.2021.8.1.524 67 6878 69 70Table 1: Partial estimation results 71 72 73January 2017—December 2020 74January 2017—March 2020 75April 2020—December 2020 760.25Q 770.50Q 780.75Q 79OLS 800.25Q 810.50Q 820.75Q 83OLS 840.25Q 850.50Q 860.75Q 87OLS 88lnairbnb 890.0303 900.0310 910.0244 920.0297 930.0308 940.0322 950.0247 960.0306 970.0183 980.0219 990.0233 1000.0228 101(0.0015) (0.0014) (0.0016) (0.0014) (0.0016) (0.0015) (0.0018) (0.0015) (0.0046) (0.0044) (0.0046) (0.0040) 102characteristics 103controls 104yes 105yes 106 107yes 108 109yes 110 111yes 112 113yes 114 115yes 116 117yes 118 119yes 120 121yes 122 123yes 124 125yes 126 127area effects 128yes 129yes 130yes 131yes 132yes 133yes 134yes 135yes 136yes 137yes 138yes 139yes 140time effects 141yes 142 143yes 144 145yes 146 147yes 148 149yes 150 151yes 152 153yes 154 155yes 156 157yes 158 159yes 160 161yes 162 163yes 164 165N 16641246 16741246 16841246 16941246 17035824 17135824 17235824 17335824 1745422 1755422 1765422 1775422 178R2 1790.8184 1800.8170 1810.8156 182Source: Authors. 183 184185186===== PAGE 8 (score 0, numeric-paren 0, table-words 0, var-words 0) =====187188Volume 8 | Issue 1 | 2021 | 72-84 189Available online at www.housing-critical.com 190https://dx.doi.org/10.13060/23362839.2021.8.1.524 191 19279 193 194Conclusion 195 196There are few economic studies on the impact of pandemics on the housing market, and none 197has addressed the role of the short-term rental market. This paper helps fill this gap by 198investigating the dynamics of housing prices and rents in Warsaw before and during the Covid-19919 pandemic. Using hedonic indexes, we found a slight increase in prices and a substantial drop 200in long-term rents between March 2020 and December 2020. The shrinking Airbnb market 201increased the supply in the long-term rental market, which at least partially explains the rent 202decrease. This is indicated by the spatial variation in rent declines and by the elasticity 203identified, which indicates a positive relationship between rents and Airbnb supply. 204 205 206Funding 207 208This study is based on research project financed by the National Science Centre of Poland (grant 209no. 2017/27/B/HS4/01848). 210 211 212213214===== PAGE 10 (score 276, numeric-paren 224, table-words 2, var-words 2) =====215216Volume 8 | Issue 1 | 2021 | 72-84 217Available online at www.housing-critical.com 218https://dx.doi.org/10.13060/23362839.2021.8.1.524 219 22081 221 222Appendix B 223 224Table B1: Regression estimation results 225 226 227January 2017 - December 2020 228January 2017- March 2020 229April 2020 – December 2020 2300.25Q 2310.50Q 2320.75Q 233OLS 2340.25Q 2350.50Q 2360.75Q 237OLS 2380.25Q 2390.50Q 2400.75Q 241OLS 242Const 2437.0818 2447.1488 2457.3370 2467.1012 2477.0969 2487.1538 2497.3570 2507.1158 2517.0173 2527.0874 2537.1793 2547.0122 255(0.0183) 256(0.0163) 257(0.0191) 258(0.0161) 259(0.0194) 260(0.0172) 261(0.0206) 262(0.0172) 263(0.0555) 264(0.0510) 265(0.0530) 266(0.0468) 267age 268-0.0068 269-0.0074 270-0.0076 271-0.0049 272-0.0070 273-0.0073 274-0.0076 275-0.0050 276-0.0056 277-0.0074 278-0.0074 279-0.0046 280(0.0001) 281(0.0001) 282(0.0001) 283(0.0001) 284(0.0001) 285(0.0001) 286(0.0001) 287(0.0001) 288(0.0003) 289(0.0002) 290(0.0002) 291(0.0002) 292age2 2930.0001 2940.0001 2950.0001 2960.0001 2970.0001 2980.0001 2990.0001 3000.0001 3010.0000 3020.0001 3030.0001 3040.0001 305(0.0000) 306(0.0000) 307(0.0000) 308(0.0000) 309(0.0000) 310(0.0000) 311(0.0000) 312(0.0000) 313(0.0000) 314(0.0000) 315(0.0000) 316(0.0000) 317area 3180.0153 3190.0167 3200.0181 3210.0172 3220.0150 3230.0165 3240.0179 3250.0169 3260.0167 3270.0180 3280.0200 3290.0188 330(0.0001) 331(0.0001) 332(0.0001) 333(0.0001) 334(0.0001) 335(0.0001) 336(0.0001) 337(0.0001) 338(0.0003) 339(0.0003) 340(0.0003) 341(0.0003) 342lnairbnb 3430.0303 3440.0310 3450.0244 3460.0297 3470.0308 3480.0322 3490.0247 3500.0306 3510.0183 3520.0219 3530.0233 3540.0228 355(0.0015) 356(0.0014) 357(0.0016) 358(0.0014) 359(0.0016) 360(0.0015) 361(0.0018) 362(0.0015) 363(0.0046) 364(0.0044) 365(0.0046) 366(0.0040) 367lncc 368-0.0800 369-0.0960 370-0.1305 371-0.1125 372-0.0799 373-0.0944 374-0.1302 375-0.1111 376-0.0894 377-0.1088 378-0.1359 379-0.1232 380(0.0024) 381(0.0021) 382(0.0025) 383(0.0021) 384(0.0026) 385(0.0023) 386(0.0027) 387(0.0023) 388(0.0065) 389(0.0060) 390(0.0063) 391(0.0055) 392lnsubway 393-0.0179 394-0.0168 395-0.0179 396-0.0123 397-0.0191 398-0.0181 399-0.0191 400-0.0137 401-0.0066 402-0.0060 403-0.0082 404-0.0024 405 406(0.0014) 407(0.0012) 408(0.0012) 409(0.0012) 410(0.0015) 411(0.0012) 412(0.0013) 413(0.0012) 414(0.0043) 415(0.0038) 416(0.0036) 417(0.0035) 418lnuga 419-0.0043 420-0.0069 421-0.0130 422-0.0093 423-0.0037 424-0.0070 425-0.0139 426-0.0091 427-0.0100 428-0.0066 429-0.0065 430-0.0115 431(0.0012) 432(0.0011) 433(0.0012) 434(0.0011) 435(0.0013) 436(0.0011) 437(0.0013) 438(0.0011) 439(0.0035) 440(0.0033) 441(0.0033) 442(0.0030) 443quality 4440.0456 4450.0462 4460.0417 4470.0520 4480.0458 4490.0473 4500.0427 4510.0521 4520.0469 4530.0418 4540.0340 4550.0504 456(0.0015) 457(0.0013) 458(0.0016) 459(0.0013) 460(0.0016) 461(0.0014) 462(0.0018) 463(0.0014) 464(0.0041) 465(0.0038) 466(0.0038) 467(0.0035) 468q2 469-0.0173 470-0.0131 471-0.0079 472-0.0068 473-0.0162 474-0.0121 475-0.0070 476-0.0071 477(0.0045) 478(0.0041) 479(0.0049) 480(0.0040) 481(0.0044) 482(0.0040) 483(0.0049) 484(0.0040) 485q3 4860.0417 4870.0393 4880.0488 4890.0389 4900.0412 4910.0398 4920.0505 4930.0390 494(0.0054) 495(0.0049) 496(0.0059) 497(0.0049) 498(0.0053) 499(0.0048) 500(0.0059) 501(0.0048) 502q4 5030.0408 5040.0347 5050.0344 5060.0394 5070.0402 5080.0343 5090.0356 5100.0394 511(0.0040) 512(0.0037) 513(0.0044) 514(0.0036) 515(0.0040) 516(0.0036) 517(0.0044) 518(0.0036) 519q5 5200.0275 5210.0216 5220.0269 5230.0273 5240.0264 5250.0217 5260.0264 5270.0270 528(0.0043) 529(0.0040) 530(0.0047) 531(0.0039) 532(0.0043) 533(0.0039) 534(0.0048) 535(0.0039) 536q6 5370.0102 538-0.0021 5390.0058 5400.0079 5410.0105 542-0.0014 5430.0051 5440.0071 545(0.0056) 546(0.0051) 547(0.0061) 548(0.0051) 549(0.0056) 550(0.0051) 551(0.0062) 552(0.0050) 553q7 5540.0346 5550.0206 5560.0212 5570.0309 5580.0345 5590.0201 5600.0210 5610.0298 562(0.0058) 563(0.0053) 564(0.0063) 565(0.0052) 566(0.0057) 567(0.0052) 568(0.0064) 569(0.0052) 570q8 5710.0390 5720.0145 5730.0062 5740.0225 5750.0389 5760.0136 5770.0056 5780.0217 579 580(0.0073) 581(0.0066) 582(0.0079) 583(0.0066) 584(0.0072) 585(0.0066) 586(0.0080) 587(0.0065) 588 589 590 591 592q9 5930.0324 5940.0204 5950.0163 5960.0210 5970.0309 5980.0197 5990.0151 6000.0197 601 602(0.0087) 603(0.0080) 604(0.0095) 605(0.0079) 606(0.0087) 607(0.0079) 608(0.0096) 609(0.0078) 610 611 612 613 614q10 6150.0253 6160.0148 6170.0021 6180.0230 6190.0245 6200.0131 6210.0042 6220.0212 623(0.0079) 624(0.0073) 625(0.0087) 626(0.0072) 627(0.0079) 628(0.0072) 629(0.0088) 630(0.0072) 631q11 6320.0418 6330.0385 6340.0394 6350.0337 6360.0400 6370.0368 6380.0380 6390.0320 640(0.0079) 641(0.0072) 642(0.0086) 643(0.0071) 644(0.0078) 645(0.0071) 646(0.0087) 647(0.0071) 648q12 6490.0283 6500.0224 6510.0206 6520.0207 6530.0276 6540.0216 6550.0194 6560.0190 657(0.0093) 658(0.0085) 659(0.0101) 660(0.0084) 661(0.0092) 662(0.0083) 663(0.0102) 664(0.0083) 665q13 6660.0437 6670.0276 6680.0218 6690.0320 6700.0419 6710.0257 6720.0227 6730.0307 674(0.0086) 675(0.0078) 676(0.0093) 677(0.0077) 678(0.0085) 679(0.0077) 680(0.0094) 681(0.0077) 682q14 683-0.0214 684-0.0200 685-0.0286 686-0.0272 687(0.0075) 688(0.0068) 689(0.0081) 690(0.0068) 691q15 692-0.0249 693-0.0173 694-0.0078 695-0.0218 696-0.0012 6970.0072 6980.0124 6990.0055 700(0.0078) 701(0.0071) 702(0.0085) 703(0.0070) 704(0.0106) 705(0.0100) 706(0.0103) 707(0.0091) 708q16 709-0.0381 710-0.0208 711-0.0042 712-0.0185 713-0.0207 7140.0029 7150.0199 7160.0034 717(0.0050) 718(0.0046) 719(0.0055) 720(0.0046) 721(0.0094) 722(0.0087) 723(0.0088) 724(0.0080) 725N 72641246 72741246 72841246 72941246 73035824 73135824 73235824 73335824 7345422 7355422 7365422 7375422 738R2 7390.8184 7400.8170 7410.8156 742Source: Authors. 743 744 745746747===== PAGE 11 (score 10, numeric-paren 0, table-words 1, var-words 8) =====748749Volume 8 | Issue 1 | 2021 | 72-84 750Available online at www.housing-critical.com 751https://dx.doi.org/10.13060/23362839.2021.8.1.524 752 75382 754 755Table B2: A description of the variables 756 757Symbol 758Description 759q1, …., q16 76016-time dummy variables used in the global model. If the dwelling 761was sold in a given year-quarter, it takes the value 1; otherwise, it 762takes 0. 763area 764area of dwelling 765age 766age of the building in years 767uga 768distance to the nearest urban green area in metres 769subway 770distance to the nearest subway station 771cc 772distance to the city centre in metres 773airbnb 774monthly number of active apartments in 775the district in which the apartment was offered for long-term rent 776quality 777quality of the apartment (values 1-5) 778Source: Authors. 779 780 781 782