p–ISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 4, No. 8, August 2023 http://jist.publikasiindonesia.id/
Doi: 10.59141/jist.v4i8.670 960
LOAN-TO-VALUE POLICY AND DEMAND FOR MORTGAGE FINANCE:
EVIDENCE FROM INDONESIA
Tomy Zulfikar, Nining Indroyono Soesilo
University of Indonesia Depok, Indonesia
Email: [email protected]
*Correspondence
ARTICLE INFO
ABSTRACT
Accepted
: 02-08-2023
Revised
: 11-08-2023
Approved
: 12-08-2023
Demand for mortgage finance showed a slowdown. And also, property
residential sales showed a slowdown. As is well known, most
consumers buy property residential is financed by mortgage finance.
Through LTV policy, the Bank of Indonesia wants to stimulate demand
for mortgage finance and also property residential sales to could boost
economic growth sustainably. A question is whether changes in the
LTV ratio could boost economic growth sustainably and whether other
factors are affecting demand for mortgage finance. This article sees the
question by considering what the impacts are in both lower-middle-
income and higher-middle-income provinces. By regressing the
statistical model Fixed Effect Model (FEM) and Random Effect Model
(REM), the result shows that LTV policy is affecting positively the
demand for mortgage finance, particularly in lower-middle-income
provinces. When the LTV ratio increased, the demand for mortgage
finance in lower-middle-income provinces is higher than the demand
for mortgage finance in higher-middle-income provinces. Moreover,
mortgage finance reflects normal goods for higher-middle-income
provinces while reflecting inferior goods for lower-middle-income
provinces. On the other hand, higher mortgage interest lowers the
demand for mortgage finance, particularly in lower-middle-income
provinces.
Keywords: Mortgage Finance;
Property Residential; LTV
Ratio.
Attribution-ShareAlike 4.0 International
Introduction
Home becomes a basic human need. Along with massive urbanization, significant
population growth and intensified land use for the central area of government, trade,
industry, and other projects caused the supply of houses to be limited. Urbanization is a
transformation from rural to industrial life (Guan, Wei, Lu, Dai, & Su, 2018).
Urbanization is considered a complex socioeconomic change. Many factors cause
urbanization, including economic, political, social, and geographical factors (Lim &
Nugraheni, 2017).
Household preferences to choose the type of house they like are limited. Factors
that influence households' preference in getting the type of house they like include: 1)
The supply of single-family housing in urban suburbs is more than the inventory of
homes in urban centers; 2) housing prices in the suburbs are more reasonable compared
to house prices in the city center; 3) Suburban houses have a lower population density
compared to downtown homes. In addition, urban centers appeal to the younger
generation regardless of preference (Lim & Nugraheni, 2017).
Loan-To-Value Policy And Demand For Mortgage Finance: Evidence From Indonesia
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, August 2023 961
Meanwhile, the demand for houses is highly dependent on economic growth and
the stability of economic conditions in a country (Andini & Falianty, 2022). Economic
growth is a very important main indicator in an economy. Strengthening economic
growth and economic stability can improve credit facilities. Meanwhile, credit facilities
and housing demand have a strong relationship (Hanişoğlu & Azer, 2017). The demand
for housing, as a basic human need, requires large funds from savings and loans. So, an
increase in mortgages has led to an increase in demand for homes (Fauzia, Rahayu, &
Nugroho, 2019).
In Q4-2019, Indonesia's real GDP growth was recorded at 4.96 percent,
continuing to slow from the highest growth of 6.50 percent since 2015 (see Figure 1.1).
Many factors cause economic growth to slow down, both from global and domestic
factors. Meanwhile, along with the slowdown in economic growth, demand for
mortgages and sales of rental properties also slowed. In quarter 4-2019, mortgage
demand growth only touched 4.95 percent year-on-year, from the highest growth of
21.52 percent in quarter 3-2013 (Ardely & Ekananda, 2022). Along with the slowdown
in mortgage demand, residential property sales also showed a slowdown. In Q4-2019,
residential property sales growth only touched 1.19 percent year-on-year, from the
highest growth of 224.01 percent in Q1-2015 (see Figure 1).
Figure 1
Indonesia's real GDP growth
4,00
4,50
5,00
5,50
6,00
6,50
7,00
1Q11
2Q11
3Q11
4Q11
1Q12
2Q12
3Q12
4Q12
1Q13
2Q13
3Q13
4Q13
1Q14
2Q14
3Q14
4Q14
1Q15
2Q15
3Q15
4Q15
1Q16
2Q16
3Q16
4Q16
1Q17
2Q17
3Q17
4Q17
1Q18
2Q18
3Q18
4Q18
1Q19
2Q19
3Q19
4Q19
%yoy
Growth Rate of Real GDP
Tomy Zulfikar, Nining Indroyono Soesilo
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, Agustus 2023 962
Figure 2
Residential Property Sales and Mortgage Requests in Indonesia
As is known, the majority of residential property purchases in Indonesia are
financed by mortgage facilities. As of quarter 4-2019, the majority of consumers buying
residential property financed by mortgages showed 76.02 percent, while the rest with
gradual cash and cash of 20.23 and 3.75 percent respectively (Indonesia, 2020) (see
Figure 1.3). Therefore, the decline in mortgage demand led to a decrease in residential
property sales.
(Abdullahi, Abbas, & Abdullahi, 2018) his research showed that one of the main
factors affecting the homeownership rate is the ease of requirements in the process of
obtaining residential property financing. The LTV ratio is part of the ease of
requirements for obtaining residential property financing. Changes in the LTV ratio will
affect changes in the down payment ratio for residential property purchases or better
known as the Down-Payment (DP) ratio (Luangaram & Thepmongkol, 2022). With a
higher LTV ratio, lower DP ratio, and increased willingness to pay from consumers,
especially low-income households. Thus, based on these arguments, Bank Indonesia
(central bank) –as an economic agent from the government side in the monetary sector–
uses Loan-to-Value (LTV) policy instruments to increase growth in mortgage demand
and also residential property sales. The LTV ratio is a ratio that shows the comparison
between the value of credit or financing provided by conventional and sharia
commercial banks to the value of collateral based on the latest assessment results such
as property at the time of credit or financing (Ayuningtyas, 2021).
-5,00
0,00
5,00
10,00
15,00
20,00
25,00
-50,00
0,00
50,00
100,00
150,00
200,00
250,00
1Q13
3Q13
1Q14
3Q14
1Q15
3Q15
1Q16
3Q16
1Q17
3Q17
1Q18
3Q18
1Q19
3Q19
%yoy
%yoy
Residential property sales (LHS) Mortgage (RHS)
Loan-To-Value Policy And Demand For Mortgage Finance: Evidence From Indonesia
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, August 2023 963
Gambar 3
Pembelian Properti Residensial
Bank Indonesia first released its LTV policy in March 2012. Bank Indonesia
implements LTV policy because it reflects on the financial crisis that occurred in the
United States in 2008. The crisis had a comprehensive impact not only on economic
activity in developed economies but also in emerging markets and developing
economies. The crisis occurred due to many non-credible debtors given (subprime
mortgages) and caused the property sector to experience a price bubble. Therefore, the
crisis is the focus of Bank Indonesia so that the surge in property prices in Indonesia
does not cause a similar price bubble that can cause an economic recession (Sasikirono,
Sumanto, Sudana, & Meidiaswati, 2019).
LTV policy is a reflection of countercyclical policy. The countercyclical policy
works when the business cycle of an economy is in contraction. So, if residential
property sales are slowing down due to slowing mortgage demand, Bank Indonesia
raises the LTV ratio to encourage mortgage demand as well as residential property
sales. In addition, LTV policy is also an implication of expansionary monetary policy so
that economic activity can immediately recover or return to a higher level when the
business cycle is deteriorating. Not only that but raising the LTV ratio is also a
reflection of Bank Indonesia's credit easing policy and better known as an
accommodative monetary policy with the aim of credit relief can increase demand.
Many studies only show that the government can control mortgage demand to
stabilize financial conditions and lower the debt ratio in households by lowering the
LTV ratio (Shin & Kim, 2017). So, reflecting on the first global financial crisis in the
United States, the bursting of the residential property price bubble caused many
developed economies to experience a recession, even the impact on developing
economies. Many countries are worried about unnaturally soaring residential property
prices. In the end, by having a large ability, the government can control the demand for
residential property by lowering the LTV ratio, so that the down payment ratio burdened
76,02%
20,23%
3,75%
KPR Tunai bertahap Tunai
Tomy Zulfikar, Nining Indroyono Soesilo
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, Agustus 2023 964
by households will be relatively high. It is expected that with the lowering of the LTV
ratio, mortgage demand will gradually shrink, and residential property prices will also
fall.
However, when the residential property industry is sluggish, there have not been
many studies that strengthen the argument that an increase in the LTV ratio can drive
mortgage demand while boosting residential property sales. Therefore, this study seeks
to identify whether an increase in the LTV ratio can increase mortgage demand and also
wants to find out if there are other factors besides the LTV ratio that affect mortgage
demand.
Meanwhile, (Tarne, Bezemer, & Theobald, 2022) in their research using a
sensitivity analysis approach confirmed that Loan-to-Value (LTV) and Debt to Income
(DTI) policies have a strong influence on the residential property market. Thus, the
policy causes housing loan debtors to move to the secondary market so it is not right on
target to control house price growth. Therefore, similar to creditors in the primary
market, housing loan creditors in the secondary market need to be regulated to
maximize the effectiveness of government policies (Kinghan, McCarthy, & O’Toole,
2022).
Method
This study used analysis units at the provincial level across Indonesia to see the
impact of LTV policies on mortgage demand. Total observations amounted to 680 units
from 34 provinces throughout Indonesia during the period of the first quarter of 2015 to
the fourth quarter of 2019.constant, β1, β2, β3 β4, β5, β6, and β7 is parametric
coefficients, and e is error.
The analysis methods used are descriptive statistical analysis and regression
analysis using the Fixed Effect Model (FEM) and Random Effect Model (REM)
methods. Descriptive statistical analysis was carried out to see the distribution of data
and the relationship between the variable value of Commercial Bank Credit to
Households for residential ownership as a variable tied to the variable value of Gross
Regional Domestic Income (GRDP) in the Real Estate sector, per Capita Income,
Residential Property Price Index (IHPR), and the average lending rate of Commercial
Banks to Households for residential ownership as a control variable.
Meanwhile, the first regression analysis method was chosen using FEM because,
in addition to conducting classical tests more supportively, this method can measure the
work of independent variables against dependent variables even though they do not have
a close (significant) relationship (Allison, 2009). Also, regression analysis using the
FEM method can explain ideally because the resulting intercepts will vary in each cross-
section but the slope does not change and the presence of dummy variables can make it
appear that there are differences in treatment between intercept data (Gujarati, 2012).
Meanwhile, the second regression model using REM and the addition of other
independent variables, namely dummy low-middle-income provinces and upper-middle-
income provinces will be tested. Dummy provinces are used as time-invariant variables
Loan-To-Value Policy And Demand For Mortgage Finance: Evidence From Indonesia
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, August 2023 965
where variables have the same influence over time. The number of dummies that are
more than one does not reduce the number of degrees of freedom so the estimation
results obtained are more efficient.
Results and Discussion
By the hypothesis that has been built, LTV policy has a strong influence on the
residential property market. Figure 4.1 shows that demand for mortgages, both in lower-
middle-income and upper-middle-income provinces, continues to increase every
quarter. The increase in mortgage demand in lower-middle-income provinces was faster
than the increase in upper-middle-income provinces. This indicates that the increase in
the LTV ratio provides a larger consumer surplus in lower-middle-income provinces
compared to upper-middle-income provinces. Meanwhile, figure 4.2 shows that each
control variable has a strong relationship to mortgage demand. Real Estate sector GDP,
per capita income, loan-to-income ratio, and CPI each have a positive relationship to
mortgage demand while mortgage interest rates have a negative relationship.
Figure 1
Changes in LTV Policy on Mortgage Demand in Lower- and Upper-Middle-
Income Provinces
Tomy Zulfikar, Nining Indroyono Soesilo
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, Agustus 2023 966
15.0
17.5
20.0
22.5
25.0
27.5
30.0
32.5
0 100 200 300 400 500 600 700 800
LTI
LOG(KPR)
15.0
17.5
20.0
22.5
25.0
27.5
30.0
32.5
14.8 15.2 15.6 16.0 16.4 16.8 17.2 17.6
LOG(IPC)
LOG(KPR)
15.0
17.5
20.0
22.5
25.0
27.5
30.0
32.5
22 24 26 28 30 32
LOG(PDRB)
LOG(KPR)
15.0
17.5
20.0
22.5
25.0
27.5
30.0
32.5
184 188 192 196 200 204 208 212
IHPR
LOG(KPR)
15.0
17.5
20.0
22.5
25.0
27.5
30.0
32.5
8.5 9.0 9.5 10.0 10.5 11.0 11.5
MR
LOG(KPR)
Figure 2
Descriptive statistics for the entire province
The positive relationship between the real estate sector GDP and per capita
income indicates that mortgages reflect normal goods. The increase in income led to an
increase in demand for mortgages. In addition, an increase in the loan-to-income ratio
and IHPR led to a larger portion of mortgage demand. Meanwhile, the increase in
mortgage rates caused a decrease in mortgage demand. This is mainly due to the
increase in mortgage interest rates above the willingness to pay from consumers. Thus,
in addition to changes in the LTV ratio, other factors can affect mortgage demand.
Figure 4.3 shows that each control variable has a strong relationship to mortgage
demand in lower-middle-income provinces. Real Estate sector GDP, per capita income,
loan-to-income ratio, and CPI each have a positive relationship to mortgage demand
while mortgage interest rates have a negative relationship.
5
6
7
8
9
10
11
12
-4 -2 0 2 4 6 8 10
LOG(PDRB)
LOG(KPR)
5
6
7
8
9
10
11
12
7.5 8.0 8.5 9.0 9.5 10.0 10.5
LOG(IPC)
LOG(KPR)
5
6
7
8
9
10
11
12
0 100 200 300 400 500 600 700 800
LTI
LOG(KPR)
Loan-To-Value Policy And Demand For Mortgage Finance: Evidence From Indonesia
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, August 2023 967
5
6
7
8
9
10
11
12
184 188 192 196 200 204 208 212
IHPR
LOG(KPR)
5
6
7
8
9
10
11
12
8.5 9.0 9.5 10.0 10.5 11.0 11.5
MR
LOG(KPR)
Figure 3
Descriptive statistics for lower-middle-income provinces
The positive relationship between the real estate sector GDP and per capita
income indicates that mortgages reflect normal goods in lower-middle-income
provinces. The increase in income led to an increase in demand for mortgages. In
addition, the increase in loan-to-income ratio and IHPR has led to a larger portion of
mortgage demand in lower-middle-income provinces. Meanwhile, the increase in
mortgage rates led to a decrease in mortgage demand in lower-middle-income
provinces. This is mainly due to the increase in mortgage rates above the willingness to
pay from consumers in lower-middle-income provinces. Thus, in addition to changes in
the LTV ratio, other factors can affect mortgage demand.
Meanwhile, figure 4.4 shows that each control variable has a strong relationship
with mortgage demand in upper-middle-income provinces. Real Estate sector GDP, per
capita income, and loan-to-income ratio each have a positive relationship to mortgage
demand while IHPR and mortgage interest rates have a negative relationship.
-8
-4
0
4
8
12
4 5 6 7 8 9 10 11
LOG(PDRB)
LOG(KPR)
-8
-4
0
4
8
12
8.8 9.2 9.6 10.0 10.4 10.8
LOG(IPC)
LOG(KPR)
-8
-4
0
4
8
12
8.8 9.2 9.6 10.0 10.4 10.8
LOG(IPC)
LOG(KPR)
Tomy Zulfikar, Nining Indroyono Soesilo
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, Agustus 2023 968
-8
-4
0
4
8
12
184 188 192 196 200 204 208 212
IHPR
LOG(KPR)
-8
-4
0
4
8
12
8.5 9.0 9.5 10.0 10.5 11.0 11.5
MR
LOG(KPR)
Figure 4
Descriptive statistics for upper-middle-income provinces
The positive relationship between the real estate sector GDP and per capita
income indicates that mortgages reflect normal goods in upper-middle-income
provinces. The increase in revenue led to an increase in demand for mortgages. In
addition, an increase in the loan-to-income ratio has led to a larger portion of mortgage
demand in upper-middle-income provinces. However, the movement of IHPR is
contrary to the demand for mortgages in upper-middle-income provinces. The decline in
IHPR led to an increase in demand for mortgages. Meanwhile, the increase in mortgage
rates led to a decrease in mortgage demand in upper-middle-income provinces. This was
mainly due to the increase in mortgage rates above the willingness to pay from
consumers in upper-middle-income provinces. Thus, in addition to changes in the LTV
ratio, other factors can affect mortgage demand.
Meanwhile, the results of panel data regression using FEM and REM to see the
impact of changes in the ratio of LTV to mortgage demand are as follows:
Table 1
Statistical Test Results of the Effect of LTV Policy on Mortgage Demand
Fixed Effect Model
Random Effect
Model
Ln (Mortgage
Demand in Lower-
Middle Income
Provinces)
Ln (Mortgage
Request in upper-
middle-income
provinces)
Ln (Mortgage
Request)
Constant
17.0696
(0.0000)
-4.3126
(0.6418)
-2.0008
(0.6208)
Ln (PDRB sektor
Real Estate)
-0.0013
(0.7287)
0.0908
(0.9083)
0.0144
(0.5006)
Ln (Per capita
income)
-1.3428
a
(0.0000)
0.8644
(0.2999)
0.7318
b
(0.0615)
Rasio Loan to
Income
0.0006
a
(0.0000)
0.0232
a
(0.0073)
0.0019
a
(0.0031)
IHPR
0.0185
a
(0.0000)
0.0069
(0.5205)
0.0100
(0.1406)
Mortgage interest
-0.0609
a
0.0319
0.0035
Loan-To-Value Policy And Demand For Mortgage Finance: Evidence From Indonesia
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, August 2023 969
rates
(0.0000)
(0.7676)
(0.9573)
DUMMY_LTV
0.0336
a
(0.0000)
-0.0189
(0.7847)
-0.0184
(0.6736)
DUMMY_PROV
1.5093
c
(0.0607)
R-squared
0.9945
0.9888
0.1619
Number of
observations
340
340
680
Catatatan:
a
significant of 1%
b
significant on 5%
c
significant on 10%
The results of the regression equation above have sufficiently established a linear
and non-linear relationship between mortgage demand, both in lower-middle-income
and upper-middle-income provinces.
First, the increase in LTV ratio and mortgage demand, especially in lower-middle-
income provinces, has a positive and significant relationship. This is by the results of
previous research: Hwang et al. (2011). However, the increase in LTV ratio and
mortgage demand, especially in upper-middle-income provinces, has a negative and
insignificant relationship.
Second, per capita income and overall mortgage demand have a positive and
significant relationship. This is by previous research: Roland E. Ubogu (1988). A 1
percent increase in per capita income led to a 0.73 percent increase in mortgage
demand. This explains that mortgages reflect normal goods for all provinces. If
revenues rise, it causes an increase in demand for mortgages.
However, per capita income and demand for mortgages, especially in lower-
middle-income provinces, have a negative and significant relationship. A 1 percent
increase in per capita income led to a 1.34 percent decrease in mortgage demand. This
explains that mortgages reflect inferior goods for lower-middle-income provinces. If
income rises, it causes a decrease in demand for mortgages.
Third, the LTI ratio and overall mortgage demand have a positive and significant
relationship. A 1 percent increase in the LTI ratio led to an increase in mortgage
demand of 0.19 percent, according to previous studies: Roland E. Ubogu (1988) and
Hwang et al (2011).
Fourth, IHPR and mortgage demand, especially in lower-middle-income
provinces, have a positive and significant relationship. This is by previous research:
Dajcman, S. (2020). A 1-level increase in IHPR caused an increase in mortgage demand
by 1.85 percent.
Fifth, mortgage rates and mortgage demand, especially in lower-middle-income
provinces, have a negative and significant relationship. This is consistent with previous
research: Follain and Dunsky (1997). A 1 percent drop in mortgage rates led to a 6.09
percent increase in mortgage demand.
Tomy Zulfikar, Nining Indroyono Soesilo
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, Agustus 2023 970
Fifth, after the policy of increasing the LTV ratio, the demand for mortgages in
lower-middle-income provinces is greater than the demand for mortgages in upper-
middle-income provinces. This is by previous research: Daodi et al (2019). Meanwhile,
table 4.2 describes intercepts in each lower-middle-income province and upper-middle-
income province. This explains how big the demand for mortgages in each province is if
there are no other factors. In lower-middle-income provinces, the provinces with the
highest demand for mortgages reflected in the highest intercepts are West Java (3.0752);
East Java (2.7150); and Banten (2.1322) while the provinces with the lowest intercepts
were West Sulawesi (-3.1297); North Maluku (-2.6642); and Maluku (-2.5363).
Table 2
intercept in lower-middle- and upper-middle-income provinces
Lower-middle-income provinces
Lower-middle-income provinces
Province
Intercept
Province
Intercept
Aceh
-0,6466
Kalimantan Timur
3,0374
Bali
1,2354
Kepri
1,8038
Banten
2,1322
Papua
1,4725
Bengkulu
-1,1048
Riau
1,1578
DIY
-0,1229
Kalimantan Utara
-8,2615
Gorontalo
-1,8878
DKI Jakarta
0,7898
Jambi
-0,0196
Jawa Barat
3,0752
Jawa Tengah
1,4963
Jawa Timur
2,7150
Kalimantan Barat
0,0009
Kalimantan Selatan
0,8504
Kalimantan Tengah
1,6939
Kepulauan Babel
-0,7837
Lampung
-0,1463
Maluku Utara
-2,6642
NTB
-0,6647
NTT
-2,2107
Papua Barat
-0,2128
Sulawesi Barat
-3,1297
Sulawesi Selatan
1,4244
Sulawesi Tengah
-0,3577
Sulawesi Tenggara
-0,4377
Sulawesi Utara
0,2139
Sumatera Barat
-0,1666
Sumatera Selatan
0,8680
Loan-To-Value Policy And Demand For Mortgage Finance: Evidence From Indonesia
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, August 2023 971
Sumatera Utara
1,3865
Maluku
-2.5363
In addition, in upper-middle-income provinces, provinces with the highest
demand for mortgages reflected in the highest intercepts are East Kalimantan (3.0374)
and Riau Islands (1.8038) while provinces with the lowest intercepts are North
Kalimantan (-8.2615) and DKI Jakarta (0.7898).
The majority of provinces in eastern Indonesia have lower intercepts compared to
western Indonesia. This indicates uneven infrastructure development throughout
Indonesia. Infrastructure development in eastern Indonesia is slower than in western
Indonesia.
Conclusion
Based on the results of this study, statistically shows that when the LTV ratio
increases, the demand for mortgages in middle-low-income provinces is greater than the
demand for mortgages in upper-middle-income provinces. In addition, other factors
affect mortgage demand, such as GDP in the Real Estate sector, per capita income,
IHPR, and mortgage interest rates. Per capita, income has a positive effect on mortgage
demand throughout the province. This explains that mortgages reflect normal goods in
all provinces. This means that an increase in revenue leads to an increase in demand for
mortgages. Meanwhile, in lower-middle-income provinces, if there are no other
influencing factors, then the provinces that have the highest demand for mortgages
reflected in the highest intercepts are West Java, East Java, and Banten while the
provinces with the lowest intercepts are West Sulawesi, North Maluku, and Maluku. In
addition, in upper-middle-income provinces, provinces with the highest demand for
mortgages reflected in the highest intercepts are East Kalimantan and Riau Islands while
provinces with the lowest intercepts are North Kalimantan and DKI Jakarta.
The majority of provinces in eastern Indonesia have lower intercepts compared to
western Indonesia. This indicates uneven infrastructure development throughout
Indonesia. Infrastructure development in eastern Indonesia is slower than in western
Indonesia. It can be seen that the contribution of the real estate sector in provinces in the
western part of Indonesia is higher than in provinces in the eastern part of Indonesia.
Reflected in the contribution of the real estate sector to GRDP, it is mainly in Banten
province, followed by the provinces of Yogyakarta Special Region and DKI Jakarta.
Meanwhile, the contribution of the real estate sector to the lowest GDP was in North
Maluku, followed by Maluku and East Kalimantan.
Tomy Zulfikar, Nining Indroyono Soesilo
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 8, Agustus 2023 972
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