Strategic Interaction Between the Agglomeration of High-Rise Buildings and the Economy of DKI Jakarta

As a capital city, Jakarta has a crucial role in controlling the national economy. Central Bureau of Statistics [1] reported that the capital city shares the most prominent economic contribution to the country, around 17 to 18 percent of the total national gross domestic product (GDP), compared to other 33 provinces across Indonesia. Jakarta’s strategic role in generating significant economic contributions highlights the importance of investigating possible supporting factors to accelerate Jakarta’s economic growth. The capital city’s economy is dominated by the tertiary sector, contributing to 78 percent of GRDP in 2018. This tertiary sector, incorporating financial services, stimulates the concentration of economic activities in the form of agglomeration, demanding commercial and office spaces in high-rise buildings.

Vertical building development, particularly in the form of high-rise buildings is highly demanded in the capital city, especially for accommodating the increasing city population and addressing the issues of land scarcity. The city government has to keep up with the fast-paced building development by making renewals of land zoning and building regulations. The regulations regarding floor area and building height limitations have been implemented since the construction of the first high-rise building in DKI Jakarta, in the 1960s. This policy has continued to be carried out to achieve effective spatial planning in pursuing sustainable development goals (SDGs).

Some studies have discovered the relationship between the presence of high-rise buildings and urban agglomeration [2-7]. In these studies, an urban agglomeration is largely affected by economic agglomeration and density agglomeration. Economic agglomeration is a spatial deposition of various economic activities in an area [8]. The urban agglomeration in DKI Jakarta occurs in line with the increase in the population of the capital city, which causes an increase in the local economic activities. The increasing local economic activities create the clusters of economic centers which are today known as Central Business Districts (CBDs). The high-rise building is a physical form of spatial accommodation of economic activities in the CBD. There are economic sectors that are accommodated explicitly by high-rise buildings, particularly businesses that are based on services, such as finance, leasing, and other services that are included in the tertiary sector businesses.

Based on the GRDP, the economy of DKI Jakarta is largely dominated by the contribution of the tertiary sector with 78 percent of GRDP in 2018. The tertiary sector is dominated by the economic activities in the service and finance subsectors; therefore, the agglomeration of the economy happens largely in high-rise buildings as the place that accommodate the economic activities in the service sector. As observed in Figure 1, the agglomeration of tertiary sector economic activities is specifically accommodated in the zone allocated for office, trade, commercial, and service building function in the provincial government land use planning map. From the figure, we can also infer that the office, trade, and service building function zoning is spread into various densities in each village and municipality.

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Source: DKI Jakarta Government

Figure 1. The city zoning masterplan of DKI Jakarta in 2030

The contribution of tertiary sector GRDP is varied across the region. The municipalities that are planned as Center Business Districts (CBD) with a higher number of high-rise buildings generate a higher contribution of tertiary sector GRDP. In this case, the tertiary sector of Central and South Jakarta generates the highest contribution to GRDP of each region, as we can see in Figure 2. The graph shows that the tertiary sector of Central Jakarta signifies the highest contribution to the GRDP of Central Jakarta with an average of 90 percent from 2007 to 2018, followed by South Jakarta with an average of 83 percent. This research defines GRDP by classifying it into 5 subsectors: 1) electricity, gas, and water; 2) trade; 3) hotel and restaurant; 4) freight and communication; 5) finance, rental, and services. All of the tertiary GRDP subsectors are assumed to be accommodated by high-rise buildings.

In investigating the relationship between high-rise buildings, density, and economic agglomeration, Barr [2-4] discovered the ‘strategic interaction’ theory, meanwhile, Buchanan [6] proved the occurrence of ‘effective density. Strategic interaction is the interaction that occurs between the developers in constructing high-rise buildings. The findings proved that the high-rise buildings “interact” with each other through the height competition. This condition occurs when the height and density (indicated by the number of floors) of the newly built high-rise buildings are defined as a positive response to the height and density of the previously built high-rise buildings. In addition, the location and the height decision of every building construction are determined by the strategic locational factors of an area [2, 3, 5]. Therefore, the strategic interactions between the buildings supported by strategic locational factors can determine the height and density of the new high-rise buildings.

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Source: Statistics Indonesia

Figure 2. The contribution of the tertiary sector to GRDP

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Source: CTBUH

Figure 3. The tallest building of DKI Jakarta

Jakarta has 1327 completed high-rise building units based on the high-rise building definition used in this study. This number of commercial offices and residential dwellings indicate the primary functions of the high-rise buildings. They are not commonly utilized for other functions. As this study focused on commercial offices and residential buildings in Jakarta, it excluded other public buildings such as churches and schools. The average height of a typical building for different functions is under 12 floors, meaning that such construction is inadequate to be categorized as a high-rise building based on the definition used in this research. As Figure 3 illustrates, Gama Tower was the tallest building in 2020, functioning as a hotel and an office. The other tall buildings serve as offices, commercial buildings (hotels or malls), and residential spaces. In other words, our data suggested that the functions of the buildings essentially serve tertiary sectors, including trading, hotel, restaurant, freight, communication, finance, rental, and service.

We analyzed our data through a strategic interaction technique comprising commercial offices and residential lodgings. Fujita and Ogawa [8] propose the concept of a city’s spatial configuration as the result of the companies’ and households’ interactions, known as strategic interactions. This interaction occurs when companies tend to choose a location for a building in the existing economic agglomeration area. Based on this premise, the new office and commercial buildings respond to the previously built office and commercial buildings in the same area [2]. Likewise, the distribution of buildings for residential spaces tends to be located within a certain proximity from the commercial office buildings to reduce workers’ transport expenditures. Guan’s [9] finding suggested that the proximity between residential and commercial buildings is driven by an economic reason: reducing transport expenses. As a result, building agglomeration occurs and creates clusters in certain areas.

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Source: Rujak Center of Urban Studies

Figure 4. Floor area ratio of the existing buildings

Figure 4 shows the mapping of building density based on the Floor Area Ratio (FAR) of the completed buildings in DKI Jakarta. The area with the darkest red color indicates that the area has FAR 3.5 and above which means it is classified as a potential area for high-rise buildings. The zone with a 3.5 FAR index means that the building in the area plotted on the zone has a maximum total floor area equal to or below 3.5 times the land lot area. The zoning in every land lot plotted by the government will define the building density in the future.

There has been no previous study of DKI Jakarta that investigate the relationship between the density clusters and the economic growth. This study analyzes the relationship between the building density clusters at the urban village as well as city levels, and the economic growth. Since there is no available valid FAR data within the period of this research, the data of the total number of floors and building height are used as the representation of the building density indicators.

Effective density (Effective density is a measure of density that was defined by the DfT. It takes into account changes in i) employment density and ii) accessibility of jobs. If either of these two factors increases, effective density will also increase.) is a condition when the existence of agglomeration of buildings and workers at a certain period triggers a positive impact on the city's productivity [6]. The increasing city productivity may indicate an increase in the effective density with the increase in building and employment density. Buchanan [6] and Curci [7] define ‘agglomeration benefit’ as the added value in form of increased productivity for each additional unit of building and employment density. 

We conducted this study in two phases. The first phase was done in the urban village to investigate the strategic interactions among high-rise buildings (commercial offices and residential functions) in Jakarta urban village. The second phase was completed on the city level to substantiate the effective density, as building and employment density positively impact GRDP in the tertiary sector. Thus, this study aimed to 1) analyze the economic and non-economic factors determining the high-rise building agglomeration in Jakarta, and 2) analyze the impact of the high-rise buildings and employment agglomeration in generating effective density in the city. We deployed econometric models as a panel dataset from 2007 to 2018.

3.2.1 Strategic interaction of commercial-office high-rise buildings

The first analysis aims to prove that strategic interactions are the cause for the agglomeration of new commercial-office high-rise buildings. Through the importance of this analysis, estimations are carried out using two dependent variables that define the quantity of constructed space in high-rise buildings as the model proposed by Barr and Luo [5]. The two dependent variables consist of the average number of floors (LAVG_off) and the highest floor (Lhighest_off_it) of commercial and office high-rise buildings built in a certain area in one year. Analysis with pooled OLS estimation method is carried out using robust standard error, to minimize the effect of heteroscedasticity. As a result, the model is structured as follows:

$L A V G_{-}$of $f_{i t} =\beta_{0}+\beta_1 L A V G\_allbuil2_{i t-2}$

$+\beta_2$ dum_AVGoff $2_{i t-2}$$+\beta_3$ Lemp_total2 ${ }_{i t-2}$

$+\beta_4percent\_tertiary_{i t}$$+\beta_5$$LGRDP\_1_{it-1}$$+\beta_6$ $LTrans+\mathcal{E}_{i t}$                      (1)

The dependent variable is investigated with the main explanatory variable, the average number of floors of high-rise buildings of all functions with a lag of 2 years in the construction period ( LAVG_allbuil2 and the dummy variable for commercial-office construction (dum_AVGoff2. The main explanatory variables of economic agglomeration are the total contribution of the tertiary sector (percent_tertiary_it) as a representation of economic agglomeration that is accommodated by high-rise buildings, the number of regional workers (Lemp_total2 , and the GRDP as a representation of the regional economy. The strategic location variable that we use is the number of transportation infrastructures within a radius of one sub-district (LTrans).

Next, the same set of variables is used to illustrate the existence of strategic interactions, in terms of competition between developers in creating the highest commercial-office high-rise building, among others.

$Lhighest_{{off }_{i t}}=\beta_0+\beta_{12}$ $Lhighest_{{allbuild2 }_\quad{ it-2 }}$

$+\beta_{22}$ dum_AVGoff $2_{i t-2}$$+\beta_{32}$ Lemp_total$2_{i t-2}$

$+\beta_{42}$ percent_tertiary ${ }_{i t}$$+\beta_{52}$ LGRDP_$1_{i t-1}+\beta_{62}$ LTrans$+\mathcal{E}_{i t}$                 (2)

Therefore, we use the data set of the highest commercial-office high-rise buildings completed in one year and one sub-district as the dependent variable. The competition among developers will be observed using the model estimation. The hypothesis will be proven true if the estimation result shows the height of new buildings is a form of a positive response to the height of the previously built buildings.

3.2.2 Strategic interaction of residential high-rise buildings

The second analysis is carried out to prove that the agglomeration of the new residential high-rise buildings in a certain area occurs in line with the demand for housing generated by human or economic activities within the surrounding high-rise buildings. We adopted the following formula based on Fujita and Ogawa's theory [8].

$\begin{aligned} \text { LAVG_resid }_{i t}=& \beta_0+\beta_{13} d u m_{-} \text {AVGresid } 2_{i t-2}+\beta_{23} d u m_{-} A V G o f f 2_{i t-2} \\ &+\beta_{33} \text { LGRDP_2 }+\beta_{43} \text { LTrans }+\varepsilon_{i t} \end{aligned}$                       (3)

The occurrence of strategic interactions in this model is tested with the main independent variables that represent high-rise buildings and economic agglomeration, as well as control variables that represent regional economic supporting facilities. To prove the hypothesis, this model uses the main explanatory variable in the form of dummy variables for residential and commercial buildings with a lag of two years. The imitation of residential buildings is coded as 1 if the newly-built high-rise buildings with two years lags in one year period has more residential function than commercial-office, zero if otherwise (dum_AVGresid2). The commercial dummy is 1 if by the two years lag and in one year, there are more new-built commercial-office buildings in a sub-county, 0 if otherwise (dum_AVGoff2).

The representative variable of economic agglomeration is GRDP. GRDP is a representation of potential economic activities at the city level. As stated in the theory of Fujita and Ogawa [8], residential buildings tend to respond to economic activity as a whole, not only in certain sectors. Therefore, we use GRDP for all sectors at the city level (LGRDP_2). 

We adopted the estimation technique from Buchanan [6], who defines public transport facilities as strategic locational support, and we used the number of transportation infrastructures within a one-sub-district radius (Ltrans).

To investigate developers’ tendency to compete in constructing the highest residential building, we used the highest number of floors of residential buildings in one year in sub-districts as the dependent variable. The following formula demonstrates the estimation of the independent and control variables.

$Lhighest\_resid_{i t}=\beta_0+\beta_{14}$ $Lhighest\_allbuild 2_{i t-2}$ $+\beta_{24}$ $LTrans_{i t-2}+\beta_{34} L G R D P_2+\varepsilon_{i t}$                  (4)

The model is adapted from Barr [2], who found that there was a positive relationship between the new highest building height with the previous highest building. Therefore, we use the height of the highest building for all functions with two years lag as the main explanatory variable, to measure the impact of the height decision of residential high-rise buildings.

3.2.3 Effective density: The impact of the agglomeration of high-rise buildings on the tertiary sector GRDP

We do the third analysis to find out the occurrence of effective density in DKI Jakarta: the condition when the commercial-office high-rise buildings and employment density have a positive effect on the development of the tertiary sector GRDP.

$LGRDP\_ter _{i t}=\beta_0+\beta_{15}$ $LAVG\_{of}$ $f_{i t}+\beta_{25}$ $LAVG\_allbuild_{i t}$ $+\beta_{35}$ $Lemp\_dens_{i t}$

$+\beta_{45}$ $LGDRP\_ter 2_{i t-2}$$+\beta_{55}$ GRDP $i t+\beta_{65}$ $Ltrans_{i t}+\varepsilon_{i t}$                              (5)

Curci [7] used the growth of the tertiary sector as a representation of the agglomeration benefit. For this reason, the data of tertiary sector GRDP (LGRDP_ter) is used as the dependent variable, of which every increasing unit by the estimation is considered as an agglomeration benefit. Pooled OLS estimation is run by including robust standard error. Panel data is obtained by combining all-time series and cross-section data from five municipalities in DKI Jakarta from the 2007 to 2018 period.

In this model, the capital variable is represented by the average number of floors of high-rise buildings as an input factor for company capital (LAVG_off). The average number of floors of high-rise buildings with office and commercial functions built in one year in each municipality (average_office) is one of the main explanatory variables of this equation. This variable is considered capable of explaining its function as an input factor to produce the tertiary sector in the GRDP. The primary explanatory variable is the average number of floors for constructing all building functions (LAVG_allbuild). In addition, we deployed two control variables: the GRDP of the tertiary sector in the previous two years and the whole sector in the GRDP [5] and the number of public transportation facilities in one sub-district (Ltrans).

This study’s results demonstrated that strategic interactions occur within the development of high-rise buildings in Jakarta. The strategic interactions among high-rise buildings are inseparably entwined with an economic agglomeration. There is a continuous cycle where the previously high-rise building development and the existing economic agglomeration in a particular area will attract new high-rise buildings, creating a more significant economic agglomeration. The increase in density and economic agglomeration, resulting from strategic locational factors due to the high-rise buildings, contributes positively to the growth of the economic sector in Jakarta, particularly the tertiary sector. This finding suggested that Jakarta has managed to sustain effective density.

The first analysis proved that strategic interactions occur in developing high-rise commercial office buildings. The result showed that the development of new high-rise commercial office buildings is generated by the previously existing agglomeration of the high-rise buildings with the same function. This is because the agglomeration of existing high-rise commercial office buildings in a particular area demonstrates agglomeration economies that appeal to the new commercial office building investors. It implies a close relationship between the agglomeration of high-rise buildings and the agglomeration economies.

The second analysis revealed that strategic interactions also occur in developing high-rise residential buildings, inseparably intertwined with the supporting economic and strategic locational factors. This study uncovered that vertical residential space development and density are the market answer to the demand created by the agglomeration economies from every sector of the economy, specifically, the demand for settlements within the workplace proximity. It indicates that high-rise residential buildings respond to the housing needs generated by the firms’ local economic activities.

The finding of this study also indicated that as a supporting strategic locational factor, public transportation infrastructures have upheld their exceptional contribution to developing high-rise commercial office and residential buildings in Jakarta. The finding revealed that the proximity to the transportation infrastructures is one of the essential factors for developers in deciding the new building location and density. Thus, it is vital to integrate high-rise buildings with public transportation infrastructures to reduce transport expenses and proliferate city productivity.

The results of the third analysis confirmed that the high-rise buildings and the working population positively impact Jakarta’s GRDP in the tertiary sector. Based on these results, building agglomeration instigates increased productivity in the accommodated sectors. The increasing GRDP in the tertiary sector coincides with increasing density, called the agglomeration benefit. The positive relationships between building and employment density and city productivity indicate that Jakarta experiences effective density.

Nonetheless, the major limitation of this study is the absence of spatial analysis to examine the spatial interaction among locations. Moreover, the variables used in this research are limited to the average number of floors and height of high-rise buildings built at both village and municipality levels without considering the exact building locations. More work will need to be done in spatial analysis to describe the relationships between each building’s location, spatial pattern, character, and regional connectivity. There is, therefore, a definite need for advanced research development with spatial analysis in the future, to aid the government and city planners in city development-related decision-making.