One of the driving factors for the large amount of zakat or charitable donations in Islamic countries is religion (Opoku, 2013). In the al-Qur’an there are several verses that explain about zakat, one of which is the Surah al-Taubah verse 103.

خُذۡ مِنۡ اَمۡوَالِهِمۡ صَدَقَةً تُطَهِّرُهُمۡ وَتُزَكِّيۡهِمۡ بِهَا وَصَلِّ عَلَيۡهِمۡ‌ؕ اِنَّ صَلٰوتَكَ سَكَنٌ لَّهُمۡ‌ؕ وَاللّٰهُ سَمِيۡعٌ عَلِيۡمٌ

Meaning: “Of their goods, take alms, that so thou mightest purify and sanctify them; and pray on their behalf. Verily thy prayers are a source of security for them: And Allah is One Who heareth and knoweth”.

The verse explains that the zakat payment is intended to clean up his assets because some of the assets gained are the rights of the poor. It is stated that the payment of zakat is obliged to every Muslim whose wealth reached nisab.

Etymologically, zakat is rooted from zakka-yuzakki-tazkiyatan, which means growth, purification and blessing. In terminology, zakat is an obligation imposed on one’s work, whether done alone or jointly which generates income and fulfills the nisab (Harahap, 2021). The object of zakat is assets, such as agricultural products, gold, silver, livestock and merchandise. In determining zakat there are several conditions that must be met, namely ownership, has the potential to increase, does not have debt and ownership has lasted for one year (Aisha, 2019).

Zakat is a tool of wealth distribution from wealthy people to 8 recipients of zakat, such as the needy, the poor, amil, mu’alaf, slaves, gharimin, fii sabilillah and ibnu sabil (Rizal et al., 2020). In addition, zakat is also a major pillar of the Islamic economic system that is based on good intentions and has an impact on the economy.

Economic growth is a condition where people achieve a high standard of living where job opportunities are created so that people can satisfy their needs (Permatasari, 2020). Thus, people can live in prosperity as well in economics, education and health.

(Al-Haj & Ikhsan, 2021) Finds that economic growth is a process of change calculated on the basis of gross domestic product (GDP) or quantitative income. In creating economic growth there are several influencing factors, namely natural resources, organization, accumulation of capital, level of production, division of labour and technology (Sukirno, 1994).

According to an Islamic economic perspective, economic growth is intended to increase people's well-being in accordance with Islamic teachings (Al-Haj & Ikhsan, 2021). To achieve the objective, several factors are needed, including natural resources, human resources, entrepreneurship and technology (Permatasari, 2020). Moreover, Islamic economic growth pays more attention to human development because the objectives to be attained are not only the world, but also the after world.

(Bayinah, 2017) concluded that there are four approaches that explain the casual relationship between zakat and economic growth: first, zakat is a determinant of economic growth; second, zakat follows economic growth; third, there is a reciprocal relationship between zakat and economic growth; fourth, the hypothesis of zakat and economic growth are interconnected.

Zakat and economic growth are also interrelated with Islamic banks (Alam Choudhury and Syafri Harahap, 2008). Because zakat is collected in Islamic banks in the form of financial instruments or Islamic projects to achieve gross domestic product (GDP). Afterwards, GDP is influenced by zakat using several variables, namely consumer spending, investment spending and government spending (Alam Choudhury and Syafri Harahap, 2008). If the GDP increases, it indicates that the country is experiencing economic growth.

The relationship between zakat and economic growth is strongly influenced by the effectiveness of the collection and distribution of zakat. Muzakki's number of payment intentions shows the amount of money collected (Khasandy & Badrudin, 2019). In addition, knowledge, attitudes, religion, motivation and income of the muzakki also affect the increase in zakat (Sedjati et al., 2018). The greater the amount of zakat funds issued by the muzakki, the greater the welfare felt by the community.

(Ben Jedidia & Guerbouj, 2021) concluded that zakat and trade openness have a positive effect on economic growth, while financial development and population growth rates have no effect on economic growth. The method used by researchers is panel data analysis with a sample of eight Islamic countries namely Senegal, Indonesia, Sudan, Malaysia, Qatar, UAE, Kuwait and Saudi Arabia in 2004-2017.

Specifically in Indonesia, to (Roisyatin & Jamaludin, 2020), zakat had a positive effect on economic growth in Indonesia in 2008-2018. The method used by researches is descriptive quantitative with secondary data samples obtained from website of the National Zakat Agency (BAZNAS) and the Central Statistics Agency (BPS). Then processed using linear regression analysis.

(Suprayitno, 2020) concluded that zakat has a positive effect on economic growth, consumption, and investment. The method used by researchers is the Error Correction Model (ECM) with sample data obtained from Government Finance Statistics, International Financial Statistics (IFS), National Amil Zakat Agency (BAZNAS), Indonesian Central Bank (BI) and the Central Statistics Agency (BPS).

(Warokka et al., 2013) concluded that zakat has a positive effect and has great potential for economic growth. The researcher’s method is a regression model with exploratory variables such as annual public capital.

(Aisha, 2019) concluded that zakat has no effect on economic growth and social welfare. The method used by researchers is a survey method which aims to find out what factors influence muzakki to pay zakat through the National Amil Zakat Agency (BAZNAS) or give directly to mustahik. Data collection was done by distributing questionnaires to 250 respondents via google sheet and then analyzed descriptively.

(Athoillah, 2018) concluded that zakat has a positive and significant effect on economic growth and poverty. Meanwhile, zakat has a negative and insignificant effect on unemployment. The method used by researchers is panel data analysis with a fixed effect model (FEM) approach to zakat and poverty samples that occurred in six provinces on the island of Java in 2001-2012.

(Bayinah, 2017) concluded that zakat has a positive effect on Islamic banks so that these institutions will contribute to economic growth in both the short and long term. The method used by the researchers is cointegration panel Vector Autoregressive (VAR), Decomposition of Variance (VD) and Impulse Response Function (IRF) with samples of zakat, Islamic banks and economic growth in 2011-2015 in ten districts or cities of West Java province.

(Fahmawati, 2019) concluded that the Human Development Index (IPM) variable had a significant effect on economic growth while the zakat, infaq, alms (ZIS) and poverty variables had no significant effect on economic growth in East Java province in 2015-2016. The method used by researchers is panel data regression analysis with a sample of twenty-five cities or regencies in East Java province in 2015-2016.

(Harahap, 2021) concluded that zakat has no effect on economic growth in the province of North Sumatra but zakat is able to reduce poverty in the province. The method used is regression analysis with the help of SPSS 23 software using a sample of ten years, namely 2009 to 2019.

Considering literature review analysis above, the working hypotheses for this research would be:

H₀ : Distribution of zakat and population growth can affect economic growth.

H₁ : Distribution of zakat and population growth cannot affect economic growth.

Due to the limited zakat data available, the authors used a sample of three Islamic countries with different levels of economic growth. Indonesia is a lower middle income country (US$ 1,026-3,995), Malaysia is an upper middle income country (US$ 3,996-12,375) and Singapore is a high income country (US$ 12,376 or more) (Espen Beer Prydz and Divyanshi Wadhwa, 2019). The sample has been adjusted to the existing zakat data. Thus, the authors can analyze the impact of zakat on economic growth by using several other growth factors.

Analysis of the effect of zakat on economic growth is based on panel data regression estimates using a combination of cross section and time series data as follows.

(1)

Information :

In(Yit) : GDP

I : country

t : year

In(PZit) : the amount of zakat funds distributed

Xit : control variable matrix

ξit : error term

υi : unobserved country-specific effect

µit : idiosyncratic error

(Gil-Garcia & Puron-Cid, 2014) concluded that the panel data model has several advantages, namely increasing sample size; provide more information and variety; more practical because it can combine observations over time; better describes the process of change in social phenomena. As such, panel data models can make for powerful and useful analyzes for research.

In this study, the dependent variable is economic growth while the independent variables are zakat and population growth.

ln (PZ) or the amount of zakat funds distributed. According to (Wang et al., 2016) the variable amount of zakat funds distributed can measure economic growth. The greater the amount of zakat funds distributed, the higher the level of economic growth.

ln (PP) or population growth rate. (Rukmana, 2012) concluded that the rate of population growth has a positive effect on economic growth because with an increase in population, the greater the number of workers and the rate of economic growth. Unlike (Astuti et al., 2017) concluded that these two variables have a negative relationship because with an increase in population, economic growth will decrease.

This study aims to determine the impact of zakat on economic growth. The method used is panel data regression estimation by combining cross section and time series data which aims to determine the quality of the impact of inseparable variables on individuals in several periods (Gil-Garcia & Puron-Cid, 2014). This method has several stages, namely estimating the panel data regression model, selecting the panel data regression model, testing the classical assumptions and testing the feasibility of the panel data regression model (Iqbal, 2015).

Tabel 2 shows the results of the descriptive statistical regression. It is known that the total data for each variable is 54. This number was obtained from a sample of three Islamic countries, namely Indonesia, Malaysia and Singapore in 2003-2020.

GDP has an average of 2.55E+15 with a standard deviation of 3.83E+15. This study uses a sample of three Islamic countries with different levels of economic growth. Lower middle income Indonesia, upper middle income Malaysia and high income Singapore.

Distribution of zakat funds has an average of 3.51E+10 with a standard deviation of 5.52E+10. This shows that the greater the zakat funds distributed, the greater the level of wealth of a country.

Population growth has an average of 93567442 with a standard deviation of 1.10E+08. This variable is a determining factor of economic growth because an increase in population growth in a country can encourage economic growth (Rukmana, 2012).

Panel Data Regression Model Estimation

The panel data estimation model has three approaches, namely the Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). The following are the regression results of the three approaches.

Panel Data Regression Model Selection

In determining the panel data estimation model, there are three tests that must be carried out, namely the chow test, hausman test and lagrange multiplier test. The following are the results of the three regression tests.

Table 7is the result of the hausman test regression. It is known that the value of the chi-square statistic is 417.568628 with a probability of 0.0000. This shows a probability value of less than 0.05 (0.0000 < 0.05). So it can be concluded that the model chosen is the Fixed Effect Model (FEM).

In this study, the lagrange multiplier test was not carried out because the results of the chow test and hausman test showed that the selected model was the Fixed Effect Model (FEM). Meanwhile, the lagrange multiplier test is used to determine between the Common Effect Model (CEM) or the Random Effect Model (REM).

Classic Assumption Test

Table 8 is the result of the multicollinearity test regression. It is known that the correlation value between PZ and PP is 0.450909385106404 while the correlation value between PP and PZ is 0.450909385106404. This shows a correlation value of less than 0.80 (0.450909385106404 < 0.80). So it can be conluded that there is no multicollinearity problem.

Table 9 is the result of the heteroscedasticity test regression. It is known that the probability value of the independent variable is greater than 0.05 (> 0.05). So it can be concluded that there is no heteroscedasticity problem.

Panel Data Regression Feasibility Test

Simultaneous Significance Test (F Test)

Partial Statistical Test (T Test)

Based on Table 4 it is known that the calculated t value of the zakat distribution variable is 4.391503, which means that it is greater than the t table value (4.391503 > 1.675). The probability value of the zakat distribution variable is 0.0001, which means it is smaller than the significance value (0.0001 < 0.05). It may therefore be concluded that the variable distribution of zakat has a positive and significant effect on economic growth. While the value of the regression coefficient of zakat distribution is 3434.087, meaning that if the level of zakat distribution increases by 1%, the economic growth rate will increase by 3434.087% cateris paribus.

Based on Table 4it is known that the calculated t value of the population growth variable is 26.21180, which means that it is greater than the t table value (26.21180 > 1.675). The probability value of the population growth variable is 0.0000, meaning that it is less than the significance value (0.0000 < 0.05). It can therefore be concluded that the population growth variable has an important positive effect on economic growth. Meanwhile, the value of the regression coefficient of population growth is 1.06E+08, meaning that if the population growth rate increases by 1%, the economic growth rate will increase by 1.06E+08% cateris paribus.

Determination Coefficient Test

Based on Table 4, it is known that the Adjusted R-squared value is 0.998015, meaning that the variable distribution of zakat and population growth of 99.8% can affect economic growth while the remaining 0.002% is influenced by other factors not examined in this study.