Empty, Emptier, Emptiest (Leeg, Leger, Leegst)

Vacancy in the Dutch office market: Driving around any city in the Netherlands will tell you the same thing. ‘For rent’ signs appear on every corner of the street. The most important issue among real estate professionals and now more and more a social problem: Empty offices in the Netherlands. The Dutch office market in the year 2011 can be characterized by a (too) high vacancy rate. Since the start of the new millennium, with the bursting of the IT bubble, there is a gap between demand and supply. This discrepancy is further enhanced by the turnaround in the economy in 2006, which eventually led to the current economic recession. More and more stakeholders mingle in the debate on the vacant offices in the Netherlands, including the media. The average vacancy rate in the research year 2009 was around 14%. This amounts over 6.3 million square meters of empty office space, or 1,260 soccer fields. The structural vacancy rate is assumed around 40%. Meanwhile, in 2011, this percentage increased even further. The future for the vacancy of offices in the Netherlands predicts no immediate improvement. The gap between supply and demand has grown so large that even a positive economic change would not close the gap. The current supply of square meters of office space covers more than the demand. If supply is added, then vacancy will directly or indirectly increase even further. To stop the growth of the vacancy a solution from public or private actors in the property market is needed. This study was performed to contribute indirectly to the debate that should lead to a decrease in vacancy in the Dutch office market. Amsterdam office market: This research focuses on the Amsterdam office market where the vacancy rate in 2009 was around 16% (already increased to 18% in 2011). With this percentage Amsterdam has the highest vacancy rate of the large office areas in the Netherlands: Utrecht 13%, Rotterdam 11% and The Hague 9%. Amsterdam is also leader in comparison to larger and comparable European capitals such as Paris (7%), Brussels (12%), Madrid (11%) and Munich (8%). Almost in every study conducted so far a snapshot of the available vacancy data was given. The sponsor of this research, Savills, had the belief that the dynamics in the vacancy rate will explain more about how vacancy in offices develops. To test this conviction and make it measurable, research question 1 was constructed: "How does the vacancy in the office market in the region of Amsterdam develop, on PC4-level, and how can these dynamics be displayed in a transparent manner?" The Region Amsterdam is set as an example, it invades the cities of Amsterdam, Amstelveen, Diemen and Duivendrecht. The region is segmented on the four digits of the postal code (PC4), so the vacancy can be viewed on a smaller scale than the usual city-level or district level. To explain the variety within the segmented PC4 areas this research was expanded by a second research question. This question creates more depth and a link between area characteristics and the vacancy rate within the PC4-area. The second research question was formulated as follows: "Which quantitative or qualitative area characteristics affect the dynamics of the vacancy in the office market, specifically in the Amsterdam region on PC4-level?" Research group: In this research the same research group was used for the research questions 1 and 2 using which was conducted from the database of Rudolf Bak, expert in real estate research. In the Amsterdam region there are 1332 office buildings that meet the requirements. The requirements optimized the research group and increased the validity. The requirements are presented below. The 1332 offices are located within 41 PC4-areas throughout the region of Amsterdam. The location of the PC4-areas are shown in Figure 2. A minimum area (NLA) of 500 m2; Not being extracted from the stock between 2004 and 2009; No significantly different or unlikely values shown (outliers); Within the PC4-area must be at least five offices located; Within the PC4-area must be at least 25,000 m2 (NLA) office space available. Vacancy matrix: The development of the vacancy in the office market in the region of Amsterdam could be determined by combining the figures of current vacancy with the figures of the dynamics in the vacancy. To equal both figures it is necessary to present both figures in percentage on PC4-level. The calculation of both percentages is shown below. Current vacancy rate = (Stock 2009 in m² / Total m²) x 100 % Dynamics vacancy = Vacancy rate 2004 – Vacancy rate 2009. To display these two rates in a clear manner the vacancy matrix, as shown in Figure 1, was based on the Growth Share Matrix of the Boston Consulting Group (BCG Matrix). The horizontal axis displays the current vacancy and the vertical axis displays the change in vacancy rates between 2004 and 2009, the dynamics. Each PC4-area has its own bubble, whose size depends on the number of square meters of office space within the PC4-area. The vacancy matrix is used as a system which provides a framework for bringing together the figures belonging to the current vacancy and the dynamics of the vacancy. By choosing the vacancy matrix it is possible to provide vacancy rates per quadrant in a structured form. In addition, by using the vacancy matrix it is possible to see which PC4-areas present opportunities, that allow development of individual maintenance or improvement strategies for each quadrant or region. When applying any strategy it is crucial to asses its effect on long-term. Especially the limitation of available funds will determine the feasibility in creating an acceptable vacancy rate within each PC4-area. It is also the question whether it is even desirable to invest in an area that is assessed negative. Knowing that there are too many square meters of office space in the market justifies this question. The translation of the vacancy matrix to a geographical image is shown in Figure 2. This map shows the distribution of the quadrants in the city, which clearly highlights that areas with different levels of appreciation can be adjacent. This confirms that reducing the scale to a PC4-level a more realistic image of the vacancy situation can be shown. For understanding the development and allocation of the vacancy within an area it is therefore important that the vacancy should be viewed on the smallest possible scale. Within this research the vacancy situation in the year 2009 is described. By applying the same methodology to underlying and/or future years, the vacancy situation for each year can be calculated, so the trend of the vacancy within each PC4-area will be visible. By entering this data into the vacancy matrix, a vacancy trend matrix can be created. This vacancy trend matrix provides even more knowledge to the vacancy in the Amsterdam region. The influence of area characteristics: From the existing literature seventeen area characteristics were selected. These characteristics were divided in subsequently the subjects accessibility, location, safety, functionality and building characteristics. The area characteristics were entered on building level for all 1332 buildings which form the research group. Of the seventeen tested area characteristics, eight characteristics show a significant impact on the vacancy rate. Only on these eight area characteristics a conclusion can be drawn because these results are not coincidental. Simple regression analysis determined how much influence each area characteristic has on the current vacancy rate. The formula associated with this regression model is as follows: Vacancy rate = Constant (B₀) Regression Coefficient (B₁) * Area characteristic. This comparison shows the change in percentage in the vacancy rate as the area characteristic changes with one step. This step is expressed in its own unit of measurement of this area characteristic. In the calculation B₀ stands for the intersection of the line with the Y-axis, B₁ for the slope of the line and Area characteristic stands for the unit of measurement of the area characteristic. The influence of area characteristics on the vacancy rate was tested on four scales, the results on PC4-level answered research question 2. The scales quadrant level, district level and building level contribute to the conclusions which are conducted on PC4-level. Figure 3 shows the results of the eight significant area characteristics. For example, when the distance between an intercity station and offices within a PC4-area increases with 1 km, the vacancy rate increases by 1.8%,. If there is no distance between an intercity station and offices within a PC4-area the vacancy rate amounts 10.3%. The statements associated with the distance to an intercity station are 89.6% reliable. Area characteristic || Influence (%) || Unit of measurement || Vacancy at 0 (%) || Reliability (%) KM to intercity railway station || 1,8 || Per kilometer || 10,3 || 89,6 Min to airport || -0,7 || Per minute || 26,4 || 88,9 KM to city centre || 1,7 || Per kilometer || 7,6 || 99,0 Safety subjective || 0,1 || Per point || 6,3 || 89,9 Safety avoidance || 0,1 || Per point || 6,7 || 93,9 Location function Area || -3,3 || Per step || 24,6 || 99,4 Location function Corrected || -3,1 || Per step || 23,7 || 99,3 Rental percentage || 0,2 || Per percent point || -1,2 || 86,6 Figure 3 Results regression analysis on area characteristics (PC4-level) A functional area, close to downtown, close to an intercity station and with a high subjective feeling of safety are within this research the main area characteristics that have a positive impact on the vacancy within an area. In current area valuation the present area characteristics play a significant role to determine the potential of the area. Future vacancy can be partly predicted by looking at the value of functionality of the area and the subjective safety. For areas, the distance to the city centre and the distance to an intercity station is given. The valuation that has been assigned to the functionality of the area and/or on the subjective safety can be improved through targeted investments. To prevent further vacancy or reduce the current vacancy, it is important that area characteristics are taken into account. Area characteristics play an important role during the selection process of housing for organizations using office space. Areas with a mix of functions (living/working/Leisure), and therefore have a presence of vitality and variety, will in almost all cases be preferred as a business location rather than mono-functional areas. If these areas are also experienced as unsafe and at a large distance from the city centre and an intercity station, the chance of renting out office space in this area will decrease even further. In future area development it is highly important that the value of area characteristics are translated into the right choices when classifying a new or renovated area. Mixing functions is necessary to avoid building for future vacancy. A combination of work, living and leisure functions must be created within an area to vitalize it for at least the next thirty years. By taking multi-functionality of an area as a starting point and realise this in a balanced manner the vacancy risk will decrease. Problems resulting from vacancy can be overcome when the influence of area characteristics are considered integrally in a very early stage of the real estate process.