STATISTICAL REFLECTIONS 7 November 2016 Housing prices, housing price index, Quarter 2 2016* Contents Introduction...1 Changes in property transactions...1 Annual price indices...2 Quarterly pure price index...2 Factors of overall price in the market of second-hand homes...2 Regional characteristics of the second-hand housing market...3 International data...3 Methodological notes...4 Introduction In the second quarter of 2016, the rise in second-hand home prices slowed down. After a 5.1% spike in the first quarter, home prices rose by only 0.7% in the second quarter. In the second quarter of 2016, the data suggest a further recovery in housing market sales. During this period sales growth was estimated at 29% compared to the same period of the previous year. The number of home sales grew only in the market of second-hand homes. The increase in the number of building permits suggests that more building projects will be started, however, its impact still cannot be detected in the sales of new homes. After the housing market crisis, house prices rose at different rates in the various settlements of the country increasing regional differences in the real estate market. An outstanding price increase was seen in Budapest, where in real terms prices were already above the pre-crisis levels in the second quarter of 2016. Changes in property transactions The growth in housing market sales also continued in the second quarter of 2016, when 29% more home sales were registered compared to the receipts of similar level of processing aggregated in the same period of the previous year. On this basis, it can be concluded that the volume of home market sales surpasses all known post 2010 figures and already approaches pre-crisis levels. Number of home sales and homes built for sale Year Home sales as a whole second-hand homes Of which: new homes Table 1 (thousand) Homes built for sale 2007 191.2.... 17.9 2008 154.1 140.0 14.1 17.4 2009 91.1 82.9 8.3 16.9 2010.3.5 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 113.8.5 3.3 3.4 2015 134.1 130.7 3.4 3.1 Q1 2 2016 58.9 57.5 1.4 1.9 In 2015, a total of 1,923 new homes were built with the purpose of selling, while 1,384 newly built homes were sold. Though the number of building permits has been rising since 2014, its effect does not yet appear in the market of new homes. Figure 1 Quarterly s in the total housing market turnover Thousand 40 35 30 25 20 15 10 5 0 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 quarter 2010 2011 2012 2013 2014 2015 2016 Received within T + days Total known sales (final until 2015) * All data of 2016 are preliminary.
2 Housing prices, housing price index, Quarter 2 2016 Statistical reflections Annual price indices In 2016, a pure price increase of 9.9% occurred in the market of second-hand homes compared to the average price level of the previous year. It means that housing prices would have been that much higher if this year the same homes had been sold as a year earlier. Meanwhile, the composition of sold dwellings shifted towards lower-value homes, slightly reducing the average price of second-hand homes actually sold, which was thus 2.3% lower than in 2015. 1 Table 2 Trends and factors of annual price s Year composition effect New homes pure total composition effect Previous year=% Second-hand homes pure (%) total 2008.7 102.2 102.9 88.6 101.8.1 2009 101.6 98.2 99.7 94.3 94.5 89.1 2010 102.9 93.6 96.3 109.8 97.9 107.5 2011 99.7 96.7 96.4 98.7 96.4.2 2012.7.0.7.4 96.2 96.6 2013 98.9 101.0 99.8 101.2 97.1 98.3 2014.3 104.4 104.7 102.6 104.2 106.9 2015 99.7 108.0 107.7.9 111.4 112.4 Q1 2 2016 93.2 108.3 101.0 89.0 109.9 97.7 2010=% 2007.0 106.5 101.2 109.1 106.2.8 2008.6 108.8 104.1 96.6 108.0 104.4 2009 97.1 106.8 103.8 91.1 102.1 93.0 2010.0.0.0.0.0.0 2011 99.7 96.7 96.4 98.7 96.4.2 2012.4 96.7 97.0 99.1 92.8 92.0 2013 99.2 97.6 96.8.3.1.4 2014 99.5 101.9 101.4 102.9 93.9 96.6 2015 99.2.1 109.2 103.8 104.6 108.6 Q1 2 2016 92.5 119.2.3 92.4 114.9 106.2 In the first half of 2016, the price of second-hand homes exceeded the 2008 nominal level and was 14.9% higher than the basis of 2010. The price of new homes has exceeded the 2015 level in 2008, and has increased by a further 8.3% since then. In 2016, new homes were 19.2% more expensive than in 2010. However, in real terms, housing prices have not yet reached the precrisis levels of 2008. After the consumer price index based deflation, on average, new homes are 10% and second-hand homes are 13% cheaper than in 2008. Quarterly pure price index In the first quarter of 2016, the 5.1% increase in second-hand housing prices was related to the housing market measures announced at the end of 2015. In the second quarter, the rise significantly decreased and amounted to only 0.7%. In the market of new homes, after a 2.5% decline in the fourth quarter of 2015, prices began to rise rapidly (5.5%) in the first quarter of 2016, then in the second quarter the rate of price increase still remained significant (3.1%). However, in case of new homes, the price increase has not yet been accompanied by the expansion of supply, thus very few observations are still available on the sale of new homes. Due to the low number of new home sales, hereinafter, we will examine only the market of second-hand homes in more detail. Figure 2 Price trend in the housing market pure price (2010=%) 125 Factors of overall price in the market of second-hand homes Previous years generally saw a significant increase in the composition index at the beginning of the year, for the time being we do not see such a thing in the sales data of quarter 1 2016 received so far: the total price is equal to the pure price along with no in the composition (%), their value reached 114.3% of the 2010 base. In the second quarter of 2016, the composition index was still pulled down by the faster incoming data of smaller settlements, therefore a substantial correction is expected in this field. Based on the observations of previous periods, it is expected that the composition index and, with it, the index of total price s will be adjusted upward as the database will be completed. 2 On the basis of currently available data, a slight pure price increase (0.7%) can be seen after filtering out the negative impact of market composition from the decreasing total price. 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 quarter 2008 2009 2010 2011 2012 2013 2014 2015 2016 Second-hand homes New homes Figure 3 Factors affecting s in the price of second-hand dwellings (2010=%) 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 2008 2009 2010 2011 2012 2013 2014 2015 2016 quarter Composition effect Pure Total 1 If we multiply the composition effect and the pure, we will get the index of total. 2 In general, there is a greater delay in receiving the data of larger settlements.
Statistical reflections Housing prices, housing price index, Quarter 2 2016 3 Regional characteristics of the second-hand housing market In the first two quarters of 2016, the rise in the price of second-hand homes continued to accelerate in Budapest: the price of an average home increased from HUF 17.4 million in 2015 to HUF 19.5 million exceeding by 25% the nominal levels measured in 2008. Because of this, the real value of homes in Budapest rose above the pre-crisis level, surpassing it by about 2.6%. Since 2015, second-hand homes have become more expensive by an average of 6.7% in the county seats as well, while prices continued to decline by 3.1% and 4.7% in the smaller towns and villages respectively. In Budapest, the square meter price of second-hand homes grew from HUF 2 thousand in 2015 to HUF 338 thousand in the first two quarters of 2016. The specific house price characteristic of county seats was less than half of it (HUF 177 thousand) and it was even lower in smaller towns at HUF 129 thousand. The square meter price (HUF 68 thousand) of village homes was less than one fifth of that of Budapest, while it was only HUF 53 thousand in villages outside agglomerations. The increase in regional price differentials can be detected also in the case of agglomerations. We have not observed such a significant increase than in the capital city and so prices have not yet reached the precrisis levels there. The only exception in this regard is the north-western sector of the Budapest agglomeration, which with its price level of over HUF 26 million is now among the most expensive areas of the country. Budapest agglomeration Second-hand housing prices in agglomerations in the first two quarters of 2016 compared to the 2008 price level (2008=%) Budapest Northern sector Eastern sector South-eastern sector Southern sector Western sector North-western sector Győr agglomeration Miskolc agglomeration Pécs agglomeration Central settlement -40-30 -20-10 0 10 20 30 40 Agglomeration Figure 4 In Budapest, house prices reached the level of 2008 in each district, however, the rate of price increase also varied in a very wide range: the largest price increase of more than 50% took place in the inner districts of Pest (districts V, VI, VII), while in this respect the Buda districts considered to be the most expensive are situated in the middle of the rankings. The outer districts of Pest were characterized by the smallest price increases of less than 10% (districts XVI XVIII and XX XXI), and in district XXIII the average price of homes sold in the first two quarters of 2016 is equal to the 2008 level. Changes in average prices compared to 2008, % Figure 5 Level and of the average prices of second-hand homes in the districts of Budapest compared to 2008 X. XXI. XX. IX. XI. XIII. VIII. XIV. IV. XXII. XIX. III. XV. XVIII. XVII. XVI. XXIII. International data The housing market index of Eurostat shows the aggregated price trends of second-hand and new flats. In the second quarter of 2016, the overall housing market index of the EU member states accounted for.4% of the 2010 base value. Within the Eurozone, the housing price index was below the EU average with a value of 101.5%. Since the first quarter of 2014, the Hungarian house price index has sharply increased, and by the beginning 2015 it was higher than in 2010 exceeding the EU average as well. In the first quarter of 2016, the Hungarian value of the house price index aggregated according to the Eurostat methodology was 114.4%. The fact that the price rises slowed down in the second quarter (.3%) is also clearly visible in the evolution of the aggregate price index. Figure 6 Combined housing price index in the European Union and Hungary (2010=%) 60 50 40 30 20 10 0 VII. VI. I. XII. 10 15 20 25 30 35 40 average prices in the first two quarters of 2016, HUF million 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 EU average Eurozone Hungary V. II. quarter
4 Housing prices, housing price index, Quarter 2 2016 Statistical reflections Quarterly housing market price index in European countries (2010=%) Table 3 Denomination Q1 2015 Q2 2015 Q3 2015 Q4 2015 Q1 2016 Q2 2016 Austria 122.2 130.1 135.4 133.1 138.7 141.8 Belgium 106.0 108.3.7.2 109.3.9 Bulgaria 93.4 94.2 93.8 96.6 97.7.4 Croatia 91.5 89.7.4.5 91.6.8 Cyprus 87.4 93.9 93.3 89.4 86.3.6 Czech Republic 103.3 104.4.7 106.8 108.0 111.0 Denmark 107.8 111.4 111.2.8 113.5 116.4 Estonia 153.9 159.0 155.9 157.2 157.0 161.9 Finland 106.2 106.9 106.5 106.4 106.7 107.8 France 99.5 99.6 101.0.2 99.8.4 Germany 116.6 119.2 119.8 121.5 122.2 125.5 Hungary 99.9 104.1 107.2 109.2 114.4.3 Iceland 135.0 138.1 139.6 142.7 145.7 148.1 Ireland 91.9 92.7.5 97.4 97.0 97.6 Italy 86.1 86.1 86.3.4.2 84.9 Latvia.3 124.5 125.0 128.1 128.8 137.3 Lithuania.8 119.4 121.2 118.7 119.7 123.4 Luxembourg 122.0 124.6 126.4 126.1 128.1 131.6 Malta 104.7.5.8.9 108.6 111.0 Netherlands 88.2 88.6.7 91.5 92.7 93.3 Norway 129.7 132.9 133.2 132.1 135.8 141.5 Poland 93.8.1.3 94.6 94.7.5 Portugal.3 93.7 93.8 94.9 96.6 99.6 Romania 84.5 83.5 82.7 84.0 86.7 89.2 Slovakia 101.5 103.5 103.6 104.7 106.6 109.4 Slovenia.4 87.4 84.3 84.3 86.1 87.7 Spain 71.9 74.8 75.3 75.3 76.4 77.7 Sweden 128.6 133.2 138.4 141.3 144.6 144.8 United Kingdom 112.1 114.5 118.3 119.7 121.0 124.6 EU average 99.7 101.4 102.6 103.0 103.8.4 Eurozone 97.1 98.7 99.5 99.7.1 101.5 Housing prices increased in most European countries. However, in Croatia, Cyprus and Italy, a smaller quarterly price decline of less than 1.0% occurred. Homes in Latvia saw an outstanding quarterly price increase of 7.0%, but home prices increased by more than 3.0% in Estonia, Lithuania and Portugal as well as in Norway also providing data here. Each of the neighbouring EU countries was characterized by price increases exceeding the EU average. In the second quarter of 2016, homes became more expensive by 1.9% in Slovenia, by 2.3% in Austria, by 2.6% in Slovakia and by 2.8% in Romania compared to the previous quarter. Methodological notes The below published housing price indices, as aggregate figures, are among the house price indices of Eurostat. 3 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 housing data 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 3 http://ec.europa.eu/eurostat/web/hicp/methodology/housing-price-statistics/house-price-index.
Statistical reflections Housing prices, housing price index, Quarter 2 2016 5 characteristics. At present, there are data series of uniform structure comparable in every respect from 2007, which make it possible to analyse s in home prices in a more detailed and exact way. The gradually completed data base still allows only preliminary information on the processes of 2016. The receipt of data for 2015 has been completed; our compilation's data for the period prior to 2016 are final. As a result of missing data, 2 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). New dwellings were separated by NAV based on benefits used to buy a new dwelling. 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, s in prices were broken down by the composition effect and pure s 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. Further data, information (links): Tables www.ksh.hu Contact details: kommunikacio@ksh.hu Contact us! Telephone: +36 1 345-6789 HUNGARIAN CENTRAL STATISTICAL OFFICE, 2016 All rights concerning the layout, graphics and design work of this publication are reserved for HCSO. Any kind of reproduction of them has to be approved by HCSO. Any secondary publication is allowed only by the indication of source.