In the first three quarters of 2020, the number of housing transactions decreased year-on-year by 18% in the new housing market and by 14% in the second-hand housing market, with a significant decline in quarter 2 and stabilization in quarter 3. Second-hand home sales did not decrease in rural CSOK beneficiary settlements. Compared to 2019, home prices rose by 2.4% in the second-hand housing market and by 6.2% in the new housing market, well below the pre-2020 trend.
Housing transactions fell mainly in the second quarter. Budapest's share continued to fall, to 18% of all property sales.
Second-hand house prices temporarily fell during the first Covid-19 wave in the second quarter and then rose again in the third quarter. In the third quarter of 2020, second-hand home prices were only 1.4% higher, but new home prices were 6% higher than a year earlier as they did not fall in quarter 2.
Despite modernizations in prior years, energy efficiency is quite low in second hand housing, data for marketed homes show. Second hand homes still use much more energy than new ones.
Housing market turnover continued to decline
A decline in housing market turnover that began in 2019 also continued in 2020: a total of 79,000 flats changed hands in the first three quarters, which is lower than the data observed a year earlier at a similar level of processing. The number of housing transactions decreased year-on-year by 18% in the new housing market and by 14% in the second-hand housing market.
People, due to Covid-19, bought fewer dwellings, primarily in the second quarter. During this period, the number of transactions decreased year-on-year by more than one-fourth. Customers became more active in the third quarter, with data received so far showing an increase compared to both the previous quarter and the previous year. Sales were probably only temporarily reduced by Covid-19.
In the second quarter, the number of home sales fell by more than 30% in Budapest and county seats, by roughly 30% in smaller cities and by 16% in villages, while the rural CSOK beneficiary settlements saw no change year-on-year.
Budapest's share of the housing market has been steadily declining since 2014. Budapest's share of all registered housing transactions decreased to 20% in 2019 and to a preliminary 18% in 2020. Home sales continued to grow in smaller settlements, with sales in villages exceeding 29% of all housing transactions in the first three quarters of 2020.
Market rearrangement is driven by several government measures. In June and July 2019, high-yield retail savings government bonds (Magyar Állampapír Plusz) and new housing subsidy schemes (CSOK subsidies for rural and second hand housing) were introduced, significantly reducing speculative demand in larger cities and strongly enhancing demand for rural properties.
The share of new homes in the housing market has gradually increased since 2016, reaching 7.2% in 2019. In 2020, 4.3% of known sales were related to newly built dwellings.
Number of home sales and homes built for sale
| Year, quarter | Home sales, total | Of which: | New homes built for sale | |
|---|---|---|---|---|
| second-hand homes | new homes | |||
| 2007 | 191.2 | .. | .. | 17.9 |
| 2008 | 154.1 | 140.0 | 14.1 | 17.4 |
| 2009 | 91.1 | 82.9 | 8.3 | 16.9 |
| 2010 | 90.3 | 85.5 | 4.8 | 10.7 |
| 2011 | 87.7 | 83.9 | 3.9 | 4.8 |
| 2012 | 86.0 | 83.3 | 2.6 | 3.5 |
| 2013 | 88.7 | 86.4 | 2.3 | 3.2 |
| 2014 | 113.8 | 110.5 | 3.3 | 3.4 |
| 2015 | 134.1 | 130.7 | 3.4 | 3.1 |
| 2016 | 146.3 | 141.4 | 4.9 | 5.2 |
| 2017 | 153.8 | 147.7 | 6.1 | 7.3 |
| 2018 | 163.7 | 154.6 | 9.1 | 9.5 |
| 2019 | 157.0 | 145.8 | 11.2 | 12.1 |
| Quarters 1–3 2020 (preliminary) | 79.4 | 76.0 | 3.4 | 7.3 |
Annual home prices in 2020 no longer grew as fast as in previous years
Annual pure prices for second-hand homes in 2020 no longer rose as fast as in previous years. Prices indexed to 2015 rose 2.4% year-on-year as a result of significant volatility in the first three quarters.
In the first three quarters of 2020, new home prices rose 6.2% year-on-year, preliminary data show.
Trends and factors of annual price change
| Year, quarter | New homes | Second-hand homes | |||||
|---|---|---|---|---|---|---|---|
| composition effect |
pure change in prices |
total change in prices |
composition effect |
pure change in prices |
total change in prices |
||
| Previous year=100.0 | |||||||
| 2016 | 97.4 | 110.5 | 107.6 | 92.9 | 113.3 | 105.3 | |
| 2017 | 98.0 | 118.6 | 116.3 | 97.2 | 111.9 | 108.7 | |
| 2018 | 106.5 | 113.4 | 120.8 | 97.6 | 114.2 | 111.5 | |
| 2019 | 98.3 | 112.7 | 110.8 | 95.4 | 117.9 | 112.5 | |
| Quarters 1–3 2020 (preliminary) | 94.7 | 106.2 | 100.6 | 92.6 | 102.4 | 94.8 | |
| 2015=100.0 | |||||||
| 2015 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | |
| 2016 | 97.4 | 110.5 | 107.6 | 92.9 | 113.3 | 105.3 | |
| 2017 | 95.5 | 131.1 | 125.1 | 90.3 | 126.9 | 114.5 | |
| 2018 | 101.7 | 148.7 | 151.1 | 88.1 | 144.9 | 127.7 | |
| 2019 | 100.0 | 167.6 | 167.5 | 84.1 | 170.8 | 143.6 | |
| Quarters 1–3 2020 (preliminary) | 94.7 | 178.0 | 168.5 | 77.8 | 174.9 | 136.1 | |
CPI-adjusted real prices slightly rose (by 2.8%) in the new housing market and fell by 1.0% in the second-hand housing market, interrupting a steady rise in real prices since 2014.
Minor price correction in the second-hand housing market after the spring Covid-19 wave
Second-hand home prices rose in the first quarter of 2020, then fell by 3.4% in the second quarter, and rose by 2.3% to almost the first quarter level (178%) in the third quarter after the spring Covid-19 wave. Following market fluctuations, second-hand home prices were 1.4% higher in the third quarter of 2020 than a year earlier, a significant change from the annual growth of more than 10% in previous years.
New home prices rose by 7.1% in Q1 2020 and then did not change significantly during the year, so the base index barely moved from 178% in Q1 and did not reach 179% in Q3. In Q3, new home prices were 6.0% higher than in the same period last year.
New home prices rose with fewer transactions
In Q1–Q3 2020:
- More than 7 thousand new homes were built for sale, 28% more than a year earlier. Although housing VAT became 27% again from 2020, during this period many sales were still made using the 5% discounted VAT, helping to maintain vigorous growth. (Homes licensed before November 2018 could still be sold with reduced VAT even after the reduced VAT rate was phased out from January 2020.)
- However, demand for new housing has been dampened by the introduction of high-yield government securities (Magyar Állampapír Plusz), expectations for further housing subsidies ('rust zone VAT rebate'), and the spring wave of Covid-19.
- Due to these and lengthy administrative procedures, new home sales fell year-on-year by a preliminary 18% to 3,400 in the first three quarters.
- Buyers bought about the same number of dwellings in Budapest as in the previous year. Home prices averaged HUF 41.4 million and square meter prices averaged HUF 767 thousand, up 10% and 12%, respectively, from 2019. Square meter prices averaged HUF 882 thousand in the 9th district, where most new dwellings were sold, and HUF 723 thousand in the second ranked 13th district.
- Nearly a third of all new dwellings were sold in county seats, with square metre prices averaging HUF 448 thousand. Square meter prices averaged HUF 476 thousand in Kecskemét, HUF 424 thousand in Szombathely and HUF 528 thousand in Debrecen, all have a relatively significant new housing market.
- New housing prices averaged HUF 619 thousand per square meter in the vicinity of Lake Balaton and reached HUF 627 thousand in Siófok, exceeding the larger cities in the countryside.
Prices of new homes presented here, handed over in 2020, were largely set by contracts concluded several months, possibly a year earlier. For this reason, price level in the new housing market lags behind supply prices typical for the given period and only provides information on the price development of dwellings actually handed over.
Covid-19 has impacted most segments in the second-hand housing market
Budapest's share of the second-hand housing market has been declining since 2015. This trend continued in 2020 as well. 17% of the known sales of the first three quarters were made in Budapest. Within sales, the share of towns did not change, that of villages increased slightly and exceeded 30%. Sales of second-hand dwellings did not decrease in village CSOK beneficiary settlements. Meanwhile, 17% fewer used homes were sold in small settlements not supported by the program. The proportion of second-hand dwellings sold in CSOK beneficiary villages exceeded 28% of the total housing market, compared to around 20% or even lower in the years before the introduction of the measure.
In the first three quarters of 2020, in the second-hand housing market:
- House prices averaged 18 million forints, 600 thousand forints less than in 2019.
- Prices per square meter averaged 292 thousand forints in the first quarter, 255 thousand forints during the Covid-19 wave in the second quarter and 261 thousand forints in the third quarter, being below the first quarter level.
- Housing prices in Budapest averaged HUF 33.4 million in the third quarter, HUF 1.9 million less than in the first quarter. Home buyers were looking for smaller homes during the Covid-19 wave. Prices per square meter averaged 641 thousand forints, essentially as much as in the first quarter. Prices have dropped significantly in the most expensive neighbourhoods (hilly areas in Buda, inner districts of Pest) and slightly in other neighbourhoods.
- House prices in the county seats have hardly fallen, with prices per square meter increasing to HUF 330,000. House prices and square meter prices peaked in the first quarter in smaller settlements.
- House prices in CSOK beneficiary villages peaked at HUF 7.5 million in the first quarter, then fell to HUF 6.9 million in the second quarter and stagnated in the third.
These prices are only preliminary data, from which the final data may differ significantly. Data from larger settlements are usually received later.
Energy efficiency is low in marketed second-hand homes
Energy certificate data is a new source of statistical data on one of the most important quality characteristics of properties on the market, energy efficiency.
The database of energy certificates has been considered complete since 2017, from which time data on all completed certifications are available. Based on this, between 2017 and 2019, the number of energy certificates issued was around 150,000 per year.
Such official inspections were requested mainly in connection with real estate sales (72%), grant applications (12%), put to use permits (8.2%), other own purposes (6.0%) as well as leases and other reasons (1.9%).
Among the issued certificates, the number of inspections requested for selling or putting to use properties was highest in 2018 at 128 thousand, that is, in the year when the number of used and new dwellings sold also reached a peak (164 thousand). In 2019, when the number of housing transactions decreased by 4.1%, the number of energy certificates issued for selling or putting to use properties also declined by 8.7%.
Over three years, issued energy rating certificates did not change significantly in composition. Age of building proved to be decisive: three-quarters of dwellings built before 1960 did not reach the average quality (FF) level. Moving towards newer residential buildings, energy efficiency is gradually improving. In buildings constructed between the mid-1970s and the regime change almost 90% of dwellings already reach or exceed the average (FF) rating, to which the panel programs contributed greatly, as a large number of buildings participating in them received ‘modern’ CC and DD ratings. Among buildings after 2010, there are few average or less efficient buildings, the vast majority of properties built at that time achieved ‘modern’ (CC) or higher ratings.
Due to the unfavourable energy efficiency of old buildings, the specific primary energy consumption of buildings built before 1959 is more than three times and the primary energy demand of heating is more than four times that of new homes. In buildings with already more favorable indicators, built between 1976 and 1989, the specific primary energy consumption is still more than twice, and the primary heating energy demand is more than two and a half times higher than in new homes.
Due to unfavourable age composition, marketed second-hand dwellings are not energy efficient: their specific primary energy consumption averaging 274 kWh/m2/year, and their primary heating energy demand averaging 218 kWh /m2/ year, being almost four times and three times higher, respectively, than the corresponding indicator for a new home.
Energy demand of dwellings for sale by year of construction
| Year of construction | Specific primary consumption |
Primary energy demand for heating |
|---|---|---|
| kWh/m2/year | ||
| –1959 | 351 | 290 |
| 1960–1975 | 306 | 248 |
| 1976–1989 | 231 | 177 |
| 1990–2009 | 176 | 128 |
| 2010–2016 | 129 | 86 |
| 2017–2019 | 110 | 70 |
Most EU member states continued to see rising house prices in the third quarter
Eurostat's housing market price indices aggregate second-hand and new home prices. In the third quarter of 2020, aggregated house prices indexed for 2015 stood at 127% in EU Member States and 127% within the euro area.
In the third quarter of 2020, total house prices indexed to 2015, calculated according to Eurostat methodology, stood at 176% in Hungary, which is still the highest among the reporting countries. Most European countries have seen price increases during and after the first Covid-19 wave. In the third quarter, only Cyprus, Italy and Romania reported significant declines in house prices. House prices fell by 0.6% in the Croatian housing market and rose by more than 4% in Denmark, by more than 3% in Austria, Bulgaria and Latvia, and by almost 3% in Germany.
Among the neighbouring countries, there was little change in Slovenia (0.1%), while in Slovakia housing prices rose by 1.5% compared to the second quarter of 2020.
Quarterly nominal housing price index for individual European countries
| Denomination | 2019 | 2020 | |||||
|---|---|---|---|---|---|---|---|
| Q1 | Q2 | Q3 | Q4 | Q1 | Q2 | Q3 | |
| Austria | 122.4 | 126.4 | 127.8 | 129.8 | 131.9 | 135.0 | 139.2 |
| Belgium | 111.5 | 112.0 | 116.0 | 115.6 | 115.5 | 117.0 | 119.6 |
| Bulgaria | 129.5 | 130.3 | 132.0 | 134.0 | 135.5 | 134.1 | 138.3 |
| Croatia | 117.6 | 120.6 | 121.4 | 124.9 | 128.3 | 130.6 | 129.8 |
| Cyprus | 107.9 | 112.7 | 105.6 | 106.5 | 109.1 | 109.5 | 104.2 |
| Czech Republic | 137.2 | 140.6 | 143.4 | 146.4 | 149.0 | 151.5 | 155.4 |
| Denmark | 116.0 | 118.7 | 118.9 | 116.4 | 118.4 | 120.4 | 125.5 |
| Estonia | 122.0 | 123.1 | 126.2 | 129.8 | 136.0 | 128.1 | 131.1 |
| Finland | 103.7 | 105.3 | 104.9 | 104.2 | 105.1 | 106.1 | 106.6 |
| France | 108.5 | 109.7 | 112.3 | 112.6 | 113.8 | 115.6 | 117.9 |
| Germany | 124.6 | 127.8 | 129.6 | 132.7 | 133.5 | 135.8 | 139.7 |
| Hungary | 165.0 | 170.5 | 173.2 | 171.9 | 178.2 | 172.6 | 176.3 |
| Iceland | 146.2 | 147.2 | 148.2 | 151.7 | 153.1 | 156.3 | 159.2 |
| Ireland | 133.0 | 133.7 | 135.6 | 135.3 | 134.3 | 134.2 | 134.6 |
| Italy | 97.7 | 99.1 | 98.8 | 98.5 | 99.4 | 102.4 | 99.8 |
| Latvia | 134.0 | 140.2 | 144.6 | 144.7 | 145.8 | 142.3 | 147.6 |
| Lithuania | 129.2 | 131.1 | 132.4 | 133.8 | 137.3 | 140.3 | 140.9 |
| Luxembourg | 125.0 | 131.4 | 134.4 | 137.2 | 142.7 | 148.7 | 152.7 |
| Malta | 118.5 | 122.8 | 126.4 | 130.9 | 125.1 | 127.6 | 129.5 |
| The Netherlands | 129.7 | 131.8 | 133.4 | 135.6 | 137.8 | 141.1 | 144.6 |
| Norway | 118.5 | 121.7 | 120.5 | 120.0 | 122.2 | 125.3 | 127.9 |
| Poland | 118.3 | 121.1 | 123.6 | 127.1 | 131.7 | 134.3 | 137.1 |
| Portugal | 137.1 | 141.5 | 143.1 | 144.1 | 151.2 | 152.5 | 153.3 |
| Romania | 119.9 | 121.8 | 123.6 | 125.5 | 129.6 | 129.8 | 126.4 |
| Slovakia | 126.4 | 131.1 | 134.5 | 137.6 | 143.0 | 143.8 | 145.9 |
| Slovenia | 127.0 | 128.8 | 131.3 | 131.6 | 133.0 | 135.6 | 135.7 |
| Spain | 122.9 | 124.3 | 126.3 | 125.4 | 126.9 | 127.0 | 128.6 |
| Sweden | 115.0 | 116.5 | 118.5 | 118.7 | 120.2 | 120.3 | 123.0 |
| United Kingdom | 115.2 | 116.0 | 118.0 | 117.5 | 117.5 | 117.6 | 121.2 |
| EU average | 117.1 | 119.1 | 120.8 | 121.8 | 123.2 | 124.7 | 126.7 |
| Eurozone | 116.0 | 118.1 | 119.7 | 120.7 | 121.9 | 123.9 | 125.5 |
Methodological notes
The cumulative values of the published housing market indices are also included in the housing price indices of Eurostat.Methodology – Housing price statistics – Eurostat
[1] Due to the harmonised methodology, these data are fully comparable across the European countries as well as with the aggregated indices of the EU member states.
The source of price observations is the stamp duty database of the National Tax and Customs Administration of Hungary (NAV), from where the anonymized stamp duty data are taken over on a monthly basis directly after their receipt. All home sales concluded by private individuals are subject to this data transfer including home sale prices and the most important characteristics. Through the development, information on housing market transactions was supplemented with information available in the statistical registers of HCSO and relevant for the housing market processes. This gives us more accurate information on the type of dwellings sold on the market and their immediate environment. At present, there are data series of uniform structure comparable in every respect from 2007, which make it possible to analyse changes in home prices in a more detailed and exact way. From 2016 onwards, data received include the nationality and birth year of the given home buyer. The gradually completed data base still allows only preliminary information on the processes of 2020. Our compilation’s data for the period prior to 2020 are final.
As a result of missing data, 1 per cent of all cases were excluded from calculations. In those cases, where there were no data on the floor area of the given dwelling, but all other data were available, the floor area was estimated using the home price and its other characteristics, then we used this estimated value to further calculate. Following this, a log linear regression model was used to analyse the data. Major data used in this model: floor area of the given dwelling, character of the building, specific geographical, administrative and income indicators of the given settlement (or district in Budapest) and the characteristics of the immediate neighbourhood zone and the residential building. New dwellings were separated by NAV based on benefits used to buy a new dwelling. From 2018, data collection OSAP (National Statistical Data Collection Programme) 1078 is also used to identify new dwellings by using its data on buildings constructed for sale and received a put to use permit. The number of transactions available for monitoring the new housing market is still low in the actual period, so the preliminary nature of the results for new housing should be emphasized.
Based on the findings of the first model estimation a further 5 per cent of dwellings were filtered out as outliers from further index calculations. After the exclusion of outliers, based on repeated model estimations, changes in prices were broken down by the composition effect and pure changes in prices. As a result of the log linear method the released price indices resulted from the geometrical average of the given prices in all cases. However, the average prices of this publication are always arithmetical averages, which were calculated after the completion of the outlier filtering.
The Eurostat’s aggregated housing price index is the weighted average of the price indices of second hand homes and new homes presented in our publication. The weights are the aggregate values of home sales realized in the previous year. The most recent Hungarian data published by Eurostat are always preliminary results based on the data recorded by the end of the second month following the reference period, while to this present publication we have used data received for the complete quarter following the reference period.
The Lechner Knowledge Centre provides energy certificate data to HCSO for statistical purposes. From 2017, all issued certificates have been included in the complete database of the Lechner Knowledge Centre. Certificates issued may relate to a building or only to a specific dwelling, so their number lags behind that of housing market transactions.
Classification categories for energy certificates after 2016
| Classification | Requirement value %-a | Quality class, textual description | |
|---|---|---|---|
| AA++ | –40% | Minimal energy consumption | |
| AA+ | 40–60% | Outstanding energy efficiency | |
| AA | 61–100% | Better than near-zero energy requirements | |
| BB | 101–130% | Meets near-zero energy requirements | |
| CC | 101–130% | Modern | |
| DD | 131–160% | Almost modern | |
| EE | 161–200% | Better than average | |
| FF | 201–250% | Average | |
| GG | 251–310% | Almost average | |
| HH | 311–400% | Weak | |
| II | 401–500% | Bad | |
| JJ | 501%– | Very bad |