1# RECORD 670783d3e4613f6e96cb818330755422772653ef2# TITLE: The impact of energy certification on the real estate market: an analysis using Big Data and hedonic pricing3# YEAR: 2026.0 VENUE: Aestimum DOI: 10.36253/aestim-197114# AUTHORS: D. Vecchiato; Carolina Bonardi Pellizzari; Andrea Dominici; T. Tempesta5# PAGES: 19 CANDIDATE TABLE PAGES (1-based): [10, 12, 13, 18, 19]6# ABSTRACT: This study analyses the effect of Energy Performance Certificates (EPC) on residential buildings in Padua (Italy). Introduced by the 2002/91/EC Directive, EPCs became mandatory in European Union countries for buildings at sale or lease. Using web-scraping we collected 5,188 real estate offers in 2022 and 2023, of which 1,738 were in the ‘apartment’ category and suitable for data analysis. We examined EPC effects on prices both in aggregate terms (2022–2023 combined) and by year, to test short-run stability. Results confirm previous findings: a price premium emerges as energy classes improve, with the highest values for top EPC ratings. While most housing characteristics showed stable short-run effects, EPC classes revealed a stronger and more significant impact over time, especially for lower energy classes.789===== PAGE 1 (score 10, numeric-paren 0, table-words 0, var-words 10) =====1011Aestimum 88: 51-69, 202612Firenze University Press 13www.fupress.com/ceset14A E S T I M U M15CENTRO STUDI DI ESTIMO E DI ECONOMIA TERRITORIALE - Ce.S.E.T.16ISSN 1592-6117 (print) | ISSN 1724-2118 (online) | DOI: 10.36253/aestim-19711 17Citation: Vecchiato, D., Bonardi 18Pellizzari, C., Dominici, A. & Tempesta, 19T. (2026). The impact of energy certification 20on the real estate market and its effect 21in the short-run: an analysis using Big 22Data and hedonic pricing. Aestimum 88: 2351-69. doi: 10.36253/aestim-19711 24Received: September 23, 202525Accepted: January 23, 202626Published: September 11, 202627© 2026 Author(s). This is an open 28access, peer-reviewed article pub29lished by Firenze University Press 30(https://www.fupress.com) and distrib31uted, except where otherwise noted, 32under the terms of the CC BY 4.0 33License for content and CC0 1.0 Uni34versal for metadata.35Data Availability Statement: The 36datasets used and/or analyzed during 37the current study are available from 38the corresponding author on reason39able request.40Conflicts of Interest: The authors 41declare no conflict of interest. The 42funders had no role in the design of 43the study; in the collection, analyses, 44or interpretation of data; in the writing 45of the manuscript, or in the decision to 46publish the results.47ORCID:48DV: 0000-0002-4652-396149CBP: 0000-0002-6019-968650AD: 0000-0002-6701-085851TT: 0000-0002-6445-474452The impact of energy certification on the real 53estate market and its effect in the short-run: an 54analysis using Big Data and hedonic pricing55Daniel Vecchiato, Carolina Bonardi Pellizzari, Andrea Dominici*, 56Tiziano Tempesta57Department of Land, Environment, Agriculture and Forestry - TESAF, University of 58Padua, Italy59E-mail: daniel.vecchiato@unipd.it; carolina.bonardipellizzari@phd.unipd.it; andrea.60dominici@unipd.it; tiziano.tempesta@unipd.it61*Corresponding author62Abstract. This study analyses the effect of Energy Performance Certificates (EPC) 63on residential buildings in Padua (Italy). Introduced by the 2002/91/EC Directive, 64EPCs became mandatory in European Union countries for buildings for sale or lease. 65Using web-scraping we collected 5,188 real estate offers in 2022 and 2023, of which 661,738 were in the ‘apartment’ category and suitable for data analysis. We examined 67EPC effects on prices both in aggregate terms (2022–2023 combined) and by year, to 68test short-run stability. Results confirm previous findings: a price premium emerges as 69energy classes improve, with the highest values for top EPC ratings. While most hous70ing characteristics showed stable short-run effects, EPC classes revealed a stronger and 71more significant impact over time, especially for lower energy classes.72Keywords: appraisal, hedonic pricing, energy, energy performance certificates, big 73data, web crawling.741. INTRODUCTION75The last few decades have been marked by an unprecedented increase in 76energy consumption. According to the International Energy Agency’s (IEA) 772021 report, demand grew even more sharply after COVID-19 years. Coupled 78with pressures to adopt renewable energy sources and challenges related to 79ongoing conflicts, such as the war in Ukraine, this has led to rising energy 80prices and further pressure on the energy transition (IEA, 2021).81To reduce energy consumption while maintaining performance, various 82technologies and policies have been developed to improve energy efficiency. 83In the housing sector, energy efficiency can be translated into technologies 84to improve the sustainability of apartments, houses, or entire buildings in 85terms of energy use and CO2 emissions. Examples include solar panels, mod86ern heating systems, efficient lighting and appliances, wall insulation, and 878889===== PAGE 10 (score 91, numeric-paren 54, table-words 6, var-words 6) =====90916092Daniel Vecchiato et al.93Table 3. The hedonic models results.94 95Dependent variable: ln(P/m2)96Full sample97year=202298year=202399Constant1007.126***1017.185***1027.102***103[7.063, 7.189]104[7.100, 7.271]105[7.013, 7.191]106Surface (m2)107-0.003***108-0.003***109-0.003***110[-0.003, -0.003]111[-0.003, -0.002]112[-0.004, -0.003]113Bathrooms1140.149***1150.091***1160.170***117[0.118, 0.179]118[0.047, 0.136]119[0.129, 0.212]120Zone: Camin, Zona Industriale1210.0821220.0601230.091124[-0.017, 0.181]125[-0.102, 0.223]126[-0.036, 0.218]127Zone: Forcellini, San Camillo, Nazareth, Terranegra1280.417***1290.400***1300.441***131[0.350, 0.484]132[0.314, 0.485]133[0.342, 0.540]134Zone: Guizza, Crocifisso, Ponte Quattro Martiri, Voltabarozzo, Salboro1350.195***1360.181***1370.209***138[0.134, 0.255]139[0.102, 0.260]140[0.123, 0.296]141Zone: Piazza Mazzini, Ospedale Militare, Porta Trento, Stazione1420.402***1430.383***1440.423***145[0.319, 0.485]146[0.275, 0.490]147[0.303, 0.543]148Zone: Piazze, Duomo, Santo, Santa Sofia, Altinate, Savonarola, Ponte Molino1490.778***1500.806***1510.764***152[0.721, 0.835]153[0.731, 0.882]154[0.683, 0.845]155Zone: Sacra Famiglia, Basso Isonzo, Brusegana, Aeroporto, Paltana, Mandria1560.174***1570.175***1580.166***159[0.116, 0.232]160[0.101, 0.250]161[0.082, 0.251]162Zone: Sacro Cuore, Altichiero1630.199***1640.161***1650.234***166[0.124, 0.274]167[0.061, 0.260]168[0.128, 0.340]169Zone: Scrovegni, Portello, Ospedali, Stanga, Pio X1700.118***1710.253***1720.055173[0.052, 0.184]174[0.162, 0.344]175[-0.036, 0.146]176Zone: Specola, Riviere, San Giuseppe, San Giovanni1770.442***1780.408***1790.459***180[0.374, 0.511]181[0.308, 0.508]182[0.367, 0.551]183Zone: Torre, Mortise, Ponte di Brenta184reference185EPC: >=A1860.506***1870.473***1880.517***189[0.459, 0.553]190[0.410, 0.536]191[0.449, 0.585]192EPC: B1930.361***1940.312***1950.361***196[0.265, 0.458]197[0.202, 0.421]198[0.200, 0.522]199EPC: C2000.253***2010.183***2020.321***203[0.167, 0.339]204[0.080, 0.287]205[0.185, 0.457]206EPC: D2070.245***2080.165***2090.279***210[0.192, 0.299]211[0.089, 0.241]212[0.205, 0.352]213EPC: E2140.091***2150.077**2160.095***217[0.043, 0.139]218[0.016, 0.139]219[0.025, 0.166]220EPC: F2210.071***2220.0262230.097***224[0.029, 0.113]225[-0.032, 0.084]226[0.039, 0.155]227EPC: G228reference229Elevator (present)2300.103***2310.093***2320.093***233[0.070, 0.135]234[0.049, 0.136]235[0.047, 0.139]236Alarm System (present)2370.033*2380.087***2390.005240[-0.005, 0.070]241[0.037, 0.138]242[-0.049, 0.059]243Observations2441,7382457052461,033247R22480.5502490.6222500.529251Adjusted R22520.5452530.6122540.521255AIC256758.05525784.128258622.167259BIC260867.265261175.292262720.972263Note: 95% confidence intervals in brackets. * p < 0.10, ** p < 0.05, *** p < 0.01.264265266===== PAGE 11 (score 30, numeric-paren 0, table-words 9, var-words 12) =====26726861269The impact of energy certification on the real estate market and its effect in the short-run270price. A dwelling of EPC class >= A is worth, on aver271age, 65.8% more than a similar counterpart in class G, 272while a dwelling with a B label presents a price pre273mium of 43.5%. The influence of the EPC C, D, and E 274labels is lower, with a price premium of 28.8%, 27.8%, 275and 9.5%, respectively, compared to the G label. Class F 276has the lowest effect on the dwellings, with a price pre277mium of 7.3%. The surface of the dwelling (in m2) pre278sented a negative coefficient: this was expected and con279sistent with theory given that the dependent variable in 280our model is the price per square meter and it usually 281decreases with the dwelling size. The higher the num282ber of bathrooms, the higher the impact on real estate 283prices. Each additional bathroom increases the premium 284price by 14.9%. In the same direction, the presence of an 285elevator and an alarm system command a price premi286um of 10.8% and 3.3%, respectively. All the zone estima287tions are positive and statistically significant, except for 288“Camin, Zona Industriale”, which is not statistically sig289nificant. Since the zone of reference in our model (zone: 290“Torre, Mortise, Ponte di Brenta”) was an industrial area 291located in the north-east part of the city, results sug292gested that areas closer to the city centre present a posi293tive effect on the price given factors such as accessibility 294and prestige. The price ranges from 12.5% of the zone 295“Scrovegni, Portello, Ospedali, Stanga, Pio X” to 117.7% 296of the zone “Piazze, Duomo, Santo, Santa Sofia, Altinate, 297Savonarola, Molino”, which is the most central, histori298cal and attractive district of the city.299Regarding the second objective, namely to study the 300stability of the EPC effect in the short run, we adopted 301a sequential approach. First, we draw some general con302siderations investigating the results of the single mod303els of the two years considered (Table 3); second, we 304did a more detailed investigation to check if the results 305of the two years could be considered statistically dif306ferent (Table 5). In the second model (Table 5) all vari307ables (apart from the surface) have been interacted with 308a dummy indicating if the data were collected in 2023, 309keeping 2022 as the base level. Considering the results of 310the single models (general approach), from Table 3 it is 311possible to observe that some differences, despite being 312of small magnitude, between the two years considered 313emerge. More specifically, all EPC classes have a greater 314influence on dwelling prices in 2023 compared to 2022. 315A similar result can be observed for the number of bath316rooms, and in 5 cases out of 8 if we look at the urban 317zone. The impact on price of the presence of an elevator 318Figure 4. Plot of the coefficients estimated in Table 3. Note: the constant term was omitted because it was out of scale compared to the 319other coefficients. The dependent variable is the dwelling price, expressed as ln(P/m2). 320321322===== PAGE 12 (score 25, numeric-paren 0, table-words 5, var-words 10) =====32332462325Daniel Vecchiato et al.326is nearly unchanged between the timespan considered, 327while the presence of an alarm system has a positive 328effect in 2022, and it is not significant in 2023.329Nevertheless, checking if the results of the two years 330could be considered statistically different (detailed anal331ysis, Table 5), it is possible to notice that the dummy 332variable Year=2023 is not significant, indicating that the 333dwelling price does not depend on the year of the list334ing prices, and, therefore, that prices are not influenced 335by market dynamics or inflation between the two years. 336Looking at the stability of the EPC effect in the short 337term, from our results, it emerges that such a difference 338is significant only for some EPC classes. More specifical339ly, there is no statistically significant effect in the most 340energy efficient classes (>= A and B) with respect to G, 341while for the other classes, apart from class E, the effect 342is positive and increasing, and it ranges from 8% (class 343F) to nearly 15% (class C). It is therefore possible to 344observe that in 3 EPC classes out of 6, namely in 50 % of 345cases, there is a different effect of EPC between the two 346years examined. On the contrary, we can observe that all 347other variables have no significant differences between 348the two years, apart from the presence of an alarm sys349tem (negative effect) and one case out of 9 for what con350cerns the location of the dwelling.3515. DISCUSSION AND CONCLUSIONS352This study contributes to the growing body of 353research on the impact of energy performance cer354tificates on residential property prices, with a specific 355focus on the city of Padua, Italy. Our results confirm 356the trend found by previous authors, where the premi357um price increases passing from lower energy classes to 358the best performing EPC class, confirming the findings 359of other studies conducted on the impact of EPC on 360residential properties in Padua by Copiello and Boni361faci (2015), Copiello and Donati (2021) and Copiello 362and Coletto (2023). More in detail, from our results 363the price for an apartment presenting EPC class >= A 364is 65.8% higher compared to the worst-performing 365apartments (belonging to class G). In comparison with 366the findings reported for the city of Padua, this out367Table 4. Estimated percentage change based on the results of the hedonic models presented in Table 3.368 369Dependent variable: ln(P/m2)370% change†371(Full sample)372(year=2022)373(year=2023)374Surface (m2)375−0.309376−0.257377−0.325378Bathrooms37914.8713809.13738117.039382Zone: Camin, Zona Industriale383-384-385-386Zone: Forcellini, San Camillo, Nazareth, Terranegra38751.76938849.12338955.413390Zone: Guizza, Crocifisso, Ponte Quattro Martiri, Voltabarozzo, Salboro39121.50639219.82139323.303394Zone: Piazza Mazzini, Ospedale Militare, Porta Trento, Stazione39549.52439646.61339752.657398Zone: Piazze, Duomo, Santo, Santa Sofia, Altinate, Savonarola, Ponte Molino399117.745400124.002401114.665402Zone: Sacra Famiglia, Basso Isonzo, Brusegana, Aeroporto, Paltana, Mandria40318.97040419.17240518.085406Zone: Sacro Cuore, Altichiero40721.99440817.41740926.349410Zone: Scrovegni, Portello, Ospedali, Stanga, Pio X41112.51441228.815413-414Zone: Specola, Riviere, San Giuseppe, San Giovanni41555.65741650.40341758.229418Zone: Torre, Mortise, Ponte di Brenta419reference420EPC: >=A42165.83342260.42942367.656424EPC: B42543.50442636.55142743.475428EPC: C42928.79943020.13143137.865432EPC: D43327.77743417.90743532.130436EPC: E4379.5164388.03843910.013440EPC: F4417.323442-44310.173444EPC: G445reference446Elevator (present)44710.8204489.7214499.738450Alarm System (present)4513.3074529.139453-454Note: † For categorical and dummy variables, the percentage change was calculated using Eq. 3.455Reference levels and statistically not significant coefficients were omitted.456457458===== PAGE 13 (score 54, numeric-paren 23, table-words 6, var-words 7) =====45946063461The impact of energy certification on the real estate market and its effect in the short-run462Table 5. The hedonic models results to check if the year affects the estimated coefficients.463 464Dependent variable: ln(P/m2)465β46695% Conf. Int.467Constant4687.192***469[7.091, 7.292]470Surface (m2)471-0.003***472[-0.003, -0.003]473Bathrooms4740.122***475[0.081, 0.163]476Year = 2023477-0.096478[-0.225, 0.032]4792023 × Bathrooms4800.036481[-0.010, 0.082]482Zone483Camin, Zona Industriale4840.056485[-0.135, 0.247]486Forcellini, San Camillo, Nazareth, Terranegra4870.403***488[0.302, 0.503]489Guizza, Crocifisso, Ponte Quattro Martiri, Voltabarozzo, Salboro4900.180***491[0.087, 0.272]492Piazza Mazzini, Ospedale Militare, Porta Trento, Stazione4930.390***494[0.265, 0.516]495Piazze, Duomo, Santo, Santa Sofia, Altinate, Savonarola, Ponte Molino4960.808***497[0.720, 0.897]498Sacra Famiglia, Basso Isonzo, Brusegana, Aeroporto, Paltana, Mandria4990.179***500[0.092, 0.266]501Sacro Cuore, Altichiero5020.160***503[0.043, 0.277]504Scrovegni, Portello, Ospedali, Stanga, Pio X5050.254***506[0.148, 0.361]507Specola, Riviere, San Giuseppe, San Giovanni5080.407***509[0.290, 0.525]510Torre, Mortise, Ponte di Brenta511reference512Camin, Zona Industriale × 20235130.035514[-0.188, 0.259]515Forcellini, San Camillo, Nazareth, Terranegra × 20235160.036517[-0.100, 0.171]518Guizza, Crocifisso, Ponte Quattro Martiri, Voltabarozzo, Salboro × 20235190.031520[-0.091, 0.153]521Piazza Mazzini, Ospedale Militare, Porta Trento, Stazione × 20235220.032523[-0.135, 0.199]524Piazze, Duomo, Santo, Santa Sofia, Altinate, Savonarola, Ponte Molino × 2023525-0.050526[-0.165, 0.066]527Sacra Famiglia, Basso Isonzo, Brusegana, Aeroporto, Paltana, Mandria × 2023528-0.017529[-0.133, 0.100]530Sacro Cuore, Altichiero × 20235310.077532[-0.076, 0.229]533Scrovegni, Portello, Ospedali, Stanga, Pio X × 2023534-0.198***535[-0.334, -0.063]536Specola, Riviere, San Giuseppe, San Giovanni × 20235370.051538[-0.094, 0.195]539EPC540>=A5410.466***542[0.392, 0.540]543B5440.311***545[0.182, 0.439]546C5470.180***548[0.059, 0.301]549D5500.157***551[0.068, 0.246]552E5530.070*554[-0.002, 0.141]555F5560.022557[-0.046, 0.090]558G559reference560>=A × 20235610.053562[-0.044, 0.149]563B × 20235640.051565[-0.144, 0.247]566C × 20235670.147*568[-0.027, 0.320]569D × 20235700.124**571[0.012, 0.235]572E × 20235730.029574[-0.067, 0.125]575F × 20235760.076*577[-0.011, 0.162]578Elevator (present)5790.093***580[0.042, 0.144]5812023 × Elevator (present)5820.001583[-0.066, 0.068]584Alarm System (present)5850.089***586[0.029, 0.149]5872023 × Alarm System (present)588-0.087**589[-0.165, -0.010]590Observations5911,738592R25930.560594Adjusted R25950.550596AIC597758.230598BIC599971.190600Note: 95% confidence intervals in brackets. * p < 0.10, ** p < 0.05, *** p < 0.01.601602603===== PAGE 14 (score 6, numeric-paren 0, table-words 0, var-words 6) =====60460564606Daniel Vecchiato et al.607come is higher than that of 21.9% detected by Copiello 608and Bonifaci (2015), but it is consistent with the 61.7% 609highlighted by Copiello and Donati (2021) and with 610the band found by Copiello and Coletto (2023). Even if 611these studies have the same urban area in common with 612our application, a direct comparison of the results is 613not straightforward due to some differences. Even if all 614these studies used as data listing prices, the timing of 615data collection and the sample size were not the same. 616Moreover, we have to consider the different analyti617cal approaches implemented and the independent vari618ables included in the models. For example, Copiello and 619Bonifaci (2015) focused on residential buildings using 620listing prices collected from April to July 2013, namely 621around ten years before our application. Such a time 622gap might be one of the causes of the discrepancy of 623our results with those of the authors, since the impact 624of the EPC might have changed as a result of numer625ous dynamics over nearly a decade. Such a hypothesis 626is supported by Barreca et al. (2021), who found that, 627contrary to empirical evidence, in the first years after 628the implementation of EPC in Italy, these labels are 629increasingly exerting a significant influence on price 630variations. If the data of Copiello and Donati (2021) 631refer to around a few years before our study (third quar632ter of 2019), the authors analysed the data with a spa633tial dynamic model. Findings of Copiello and Coletto 634(2023) are referred to 2022 but are limited to a specific 635period of the year (March-July), so including 321 obser636vations. Moreover, the different analytical approaches 637implemented and the independent variables included in 638the models make it challenging to compare the results 639across studies. Lastly, it should be noted that we have 640adjusted our estimates as suggested by Halvorsen and 641Palmquist (1980) for discrete variables (see Eq. 3), and 642therefore the magnitude of the estimates, when great643er than 25%, could be even greater in the case where 644estimates were not adjusted. Our findings showed that 645while for other characteristics results could be consid646ered quite stable in the short run, for the EPC classes 647there seems to be a greater effect with time, an effect 648that proved significant for lower energy classes. Such 649a result, despite needing further validation, is quite 650interesting and could be explained with some consid651erations. First, it might well be that, as highlighted by 652Olaussen et al. (2017), the EPC, being potentially highly 653correlated with other characteristics of the building or 654dwelling, captures, along with the premium price for 655energy efficiency, other aspects related to the dwelling, 656like for example its maintenance status or whether it 657was recently renovated. In this respect, it is possible that 658old dwellings with low EPC classes were partially ren659ovated, with an improvement of the EPC class. Partial 660renovation could improve the EPC but not bring it to 661the highest levels, which could be an explanation for the 662difference between the two years found to be significant 663only for lower EPC classes, rewarding the niche market 664of partially renovated dwellings.665The observed price premiums associated with higher 666EPC ratings could serve as an incentive for homeown667ers to invest in energy-efficient upgrades and renova668tions. Beyond the potential for reducing energy costs 669and enhancing environmental sustainability, our find670ings suggest that such investments may also translate 671into tangible increases in property values. This dual ben672efit could motivate homeowners to prioritize energy effi673ciency measures, contributing to the EU’s overall goal of 674decarbonizing the building stock.675Our study suggests some lines for future research. 676First, our results should be validated given that they 677could be ‘context-dependent’ both in space and time, 678and therefore similar studies would be necessary to 679validate our results considering different cities in differ680ent periods. A further aspect that deserves attention is 681the understanding of the reliability of the use of listing 682prices in the appraisal practice, especially when using 683results in absolute values rather than relative percent684ages. In this respect, it would be interesting to scientifi685cally estimate the average discrepancy of listing prices 686from real transaction prices. For now, it is possible to 687affirm that the relative percentages of the premium pric688es derived in listing price studies could be used, subject 689to further validation, in classical appraisal approaches 690like, for example, the Market Comparison Approach. 691Such analytical effort would be particularly relevant 692given that the use of Big Data collected with the web 693crawling technique resulted particularly effective and 694therefore allows to overcome the difficulty of operat695ing with real transaction data, especially in the Italian 696or similar context, where data are available, but of dif697ficult accessibility. Furthermore, Italian data need to be 698carefully studied, given that they depend on the data 699reported in transaction documents (they are not read700ily available in a ‘database’ form), which do not follow a 701standard format, and often miss some important infor702mation like the status of the dwelling, while for exam703ple the EPC is nowadays always reported given that it is 704compulsory by law.705REFERENCES706Banca d’Italia. (2025). Sondaggio congiunturale sul mer707cato delle abitazioni in Italia. Available at: https://708709710===== PAGE 18 (score 20, numeric-paren 0, table-words 3, var-words 11) =====71171268713Daniel Vecchiato et al.714Table A1. EPC classes comparisons between the study sample and Padua Municipality residential statistics of registered EPCs. Own elabo715ration based on data available on Regione del Veneto (2025).716Energy label717Full sample718Study Sample719Municipal Registered EPCs *720year=2022721year=2023722year=2022723year=2023724n725%726n727%728n729%730n731%732n733%734>=A73541873624.173715973822.673925974025.174164974213.374392474414.8745B746427472.4748247493.4750187511.77521297532.67542217553.5756C757547583.1759297604.1761257622.47632207644.57653817666.1767D7681697699.7770587718.277211177310.877449477510.177669977711.2778E77923378013.47811067821578312778412.378579978616.47871,08578817.3789F79034579119.97921207931779422579521.87961,33079727.37981,54279924.6800G80147780227.480320980429.680526880625.98071,24780825.68091,40781022.5811all8121,738813100.0814705815100.08161,033817100.08184,868819100.08206,259821100.0822Note: * data refer to the registered EPCs in the municipality of Padua for residential buildings (Regione del Veneto, 2025) of all types 823(apartments, detached houses, etc.). The considered municipality data included all registered EPCs, not only those for buildings on sale, 824while the study sample considered only residential buildings in the apartments category for sale.825Table A2. Variance Inflation Factor (VIF) analysis related to the Full sample model reported in Table 3.826Variable827VIF8281/VIF829Surface (m2)8301.948310.515517832Bathrooms8332.018340.498356835Zone:836Camin, Zona Industriale8371.248380.808198839Forcellini, San Camillo, Nazareth, Terranegra8401.758410.572506842Guizza, Crocifisso, Ponte Quattro Martiri, Voltabarozzo, Salboro8432.058440.48838845Piazza Mazzini, Ospedale Militare, Porta Trento, Stazione8461.468470.686173848Piazze, Duomo, Santo, Santa Sofia, Altinate, Savonarola, Ponte Molino8492.848500.351695851Sacra Famiglia, Basso Isonzo, Brusegana, Aeroporto, Paltana, Mandria8522.298530.437268854Sacro Cuore, Altichiero8551.628560.618551857Scrovegni, Portello, Ospedali, Stanga, Pio X8581.828590.548833860Specola, Riviere, San Giuseppe, San Giovanni8611.798620.559873863EPC:864>=A8652.068660.486187867B8681.118690.9012870C8711.138720.88326873D8741.278750.786563876E8771.358780.738194879F8801.418810.707525882Elevator (present)8831.318840.760979885Alarm System (present)8861.18870.912921888Mean VIF8891.66890891892===== PAGE 19 (score 87, numeric-paren 51, table-words 5, var-words 7) =====89389469895The impact of energy certification on the real estate market and its effect in the short-run896Table A3. The hedonic models result considering the EPC level D as reference level.897 898Dependent variable: ln(P/m2)899Full sample900year=2022901year=2023902Constant9037.371***9047.350***9057.380***906[7.296, 7.446]907[7.247, 7.453]908[7.277, 7.484]909Surface (m2)910-0.003***911-0.003***912-0.003***913[-0.003, -0.003]914[-0.003, -0.002]915[-0.004, -0.003]916Bathrooms9170.149***9180.091***9190.170***920[0.118, 0.179]921[0.047, 0.136]922[0.129, 0.212]923Zone: Camin, Zona Industriale9240.0829250.0609260.091927[-0.017, 0.181]928[-0.102, 0.223]929[-0.036, 0.218]930Zone: Forcellini, San Camillo, Nazareth, Terranegra9310.417***9320.400***9330.441***934[0.350, 0.484]935[0.314, 0.485]936[0.342, 0.540]937Zone: Guizza, Crocifisso, Ponte Quattro Martiri, Voltabarozzo, Salboro9380.195***9390.181***9400.209***941[0.134, 0.255]942[0.102, 0.260]943[0.123, 0.296]944Zone: Piazza Mazzini, Ospedale Militare, Porta Trento, Stazione9450.402***9460.383***9470.423***948[0.319, 0.485]949[0.275, 0.490]950[0.303, 0.543]951Zone: Piazze, Duomo, Santo, Santa Sofia, Altinate, Savonarola, Ponte Molino9520.778***9530.806***9540.764***955[0.721, 0.835]956[0.731, 0.882]957[0.683, 0.845]958Zone: Sacra Famiglia, Basso Isonzo, Brusegana, Aeroporto, Paltana, Mandria9590.174***9600.175***9610.166***962[0.116, 0.232]963[0.101, 0.250]964[0.082, 0.251]965Zone: Sacro Cuore, Altichiero9660.199***9670.161***9680.234***969[0.124, 0.274]970[0.061, 0.260]971[0.128, 0.340]972Zone: Scrovegni, Portello, Ospedali, Stanga, Pio X9730.118***9740.253***9750.055976[0.052, 0.184]977[0.162, 0.344]978[-0.036, 0.146]979Zone: Specola, Riviere, San Giuseppe, San Giovanni9800.442***9810.408***9820.459***983[0.374, 0.511]984[0.308, 0.508]985[0.367, 0.551]986Zone: Torre, Mortise, Ponte di Brenta987reference988EPC: >=A9890.261***9900.308***9910.238***992[0.203, 0.319]993[0.226, 0.390]994[0.159, 0.317]995EPC: B9960.116**9970.147**9980.082999[0.013, 0.219]1000[0.024, 0.269]1001[-0.083, 0.248]1002EPC: C10030.00810040.01910050.0421006[-0.085, 0.101]1007[-0.097, 0.134]1008[-0.100, 0.185]1009EPC: D1010Reference1011EPC: E1012-0.154***1013-0.087**1014-0.183***1015[-0.214, -0.094]1016[-0.170, -0.005]1017[-0.267, -0.100]1018EPC: F1019-0.174***1020-0.138***1021-0.182***1022[-0.230, -0.119]1023[-0.219, -0.058]1024[-0.256, -0.107]1025EPC: G1026-0.245***1027-0.165***1028-0.279***1029[-0.299, -0.192]1030[-0.241, -0.089]1031[-0.352, -0.205]1032Elevator (present)10330.103***10340.093***10350.093***1036[0.070, 0.135]1037[0.049, 0.136]1038[0.047, 0.139]1039Alarm System (present)10400.033*10410.087***10420.0051043[-0.005, 0.070]1044[0.037, 0.138]1045[-0.049, 0.059]1046Observations104717381048705104910331050Adjusted R210510.54510520.61210530.5211054AIC1055758.055105684.1281057622.1671058BIC1059867.2651060175.2921061720.9721062Note: 95% confidence intervals in brackets. * p < 0.10, ** p < 0.05, *** p < 0.01.1063