THE 10th ISLAMIC BANKING, ACCOUNTING AND FINANCE INTERNATIONAL CONFERENCE 2022 (iBAF 2022)

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THE 10th ISLAMIC BANKING, ACCOUNTING AND FINANCE INTERNATIONAL CONFERENCE 2022

(iBAF 2022)

The Analysis of Factors Affecting the Development of Halal Industry in Indonesia

Dimas Bagus Wiranatakusuma

Universitas Muhammadiyah Yogyakarta, Kantor IPIEF, Gedung Pascasarjana Lantai Dasar, Kampus Terpadu UMY JL. Brawijaya, Kasihan, Bantul, Yogyakarta 55183 Indonesia

E-mail: [email protected]

Alfath Shifa Ghifara

Department of Islamic Economy, Faculty of Economic and Business, Universitas Airlangga (UNAIR), Surabaya, East Java 60286 Indonesia

Abstract

This study aims to analyze the effect of inflation, Indonesia's economic growth, and world economic growth on the development of the halal industry in Indonesia. The data used in this study are monthly for the period 2004: 1-2019: 4 taken from the Otoritas Jasa Keuangan (OJK), Bank Indonesia (BI), and the World Bank. The estimation tool used in this study is the Vector Error Correction Model (VECM) using Eviews 9. The results show that in the short-term, inflation has a significant and positive effect on the development of the halal industry in Indonesia. Indonesia's economic growth has a significant and negative impact on the development of the halal industry in Indonesia, and world economic growth has a significant and positive effect on the development of the halal industry in Indonesia. Meanwhile, in the long-term, inflation and Indonesia's economic growth have a significant and positive impact on the development of the halal industry in Indonesia, and World economic growth has a significant and negative effect on the development of the halal industry in Indonesia. The findings suggest that Indonesia takes a bottom-up approach in promoting the development of halal industry. Hence, the development of halal industry in Indonesia still depends on the society movement along with the government commitment in developing halal industry in Indonesia.

Keywords: Halal Development; Inflation; Indonesian Economic Growth; World Economic Growth; Vector Error Correction Model (VECM)

1. Introduction

The industrial sector is one of the economic sources which currently cannot be separated from economic life.

Along with the times, industrial development has begun to change from a simple stage to the present the halal industry in the industrial era 4.0, whose development has greatly increased in the world in recent years. The global halal industry can be said to be one of the sectors capable of increasing economic growth. This is evidenced by the State of Global Islamic Economic 2019, global halal industry is estimated to reach around USD 2.2 trillion (excluding the Islamic financial sector). The global halal industry is estimated to increase at an annual rate of 5.2 percent, so that this industry is predicted to be worth USD 3.2 trillion in 2024. In addition, Islamic financial assets were recorded to have reached USD 2.5 trillion in 2018.

Table 1. Total Revenue (2018) and Estimated Income (2024) in Each Halal Industry Sector

Sector Total Revenue in 2018 ($) Estimated Income in 2024 ($)

Halal Food 1.369 Billion 1.972 Billion

Modest Fashion 283 Billion 402 Billion

Media & Recreation 220 Billion 309 Billion

Muslim-Friendly Travel 189 Billion 274 Billion

Halal Pharmaceuticals 92 Billion 134 Billion

Halal Cosmetics 64 Billion 95 Billion

Islamic Finance (Assets) 2.524 Billion 3.472 Billion

Source : State of Global Islamic Economy Report 2019-2020

According to Table 1, the Islamic finance sector has the largest income among other sectors. In addition, the development of the Sharia economy in Indonesia affects the level of demand for Sharia products. The global

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market in the halal industrial sector is very high. Islamic banks also play an important role in developing Micro, Small & Medium Enterprises (Gilani et al., 2016). Sharia banks can provide Sharia financing products that are suitable for their needs, competitive, and easily accessible to Micro, Small & Medium Enterprises players engaged in the halal food industry.

The development and improvement of the halal food industry cannot be separated from the important roles that are interrelated with one another. Therefore, there is a need for the integrity of the government, society, and Islamic financial institutions to increase the competitiveness of Micro, Small & Medium Enterprises in the halal food industry sector in order to increase economic growth in Indonesia. In addition, the majority of Indonesia's population is Muslim; logically, the development of the halal industry will be even greater in Indonesia compared to other countries.

The financial sector is believed to be one of the most important sectors in supporting economic growth. This is based on Schumpeter (1911), which states that the development of the financial sector has an important role in economic growth. According to Bencivengan and Smith (1991), which strengthens the statement, it states that the development of the financial sector is a strategic factor (one of the influencing factors) that can encourage economic growth in the long term. This is because the development of the financial sector with its progress can assist small businesses in developing existing businesses so as to move the microeconomic sector within the trade circle.

Based on the above description, the inflation rate, Indonesian economic growth and world economic growth have great potential for Islamic financing, which is Islamic financing as a proxy to measure the development of the halal industry in Indonesia. Economic growth has a positive and significant impact on Islamic finance in the short and long term (Farahani and Sadr, 2012). In a research journal conducted by Furqani and Mulyany (2009), it is said that economic growth (GDP) has a positive and significant effect on Islamic financing in the long term.

Also, there is a significant relationship between economic growth and the development of Islamic finance in the short and long term (Abduh and Omar, 2012).

While, Andres, Hernando, and Salido (2002) suggest that there is an effect of inflation on economic growth through interactions with financial markets. However, from the results of research conducted by Iqbal and Nawaz (2010), it is said that high inflation will harm economic growth. This makes interested in adding the inflation variable to the study. Based on several theories found in previous studies, which will have a good impact on the development of the halal industry by using proxies for Islamic financing, so this research aims to analyze the factors that affect the growth of the Halal Industry in Indonesia.

2. Literature Review 2.1 Islamic Financing

The purpose of Islamic banking is following the principles of Sharia transactions. It shows that the activities carried out by Islamic banking can provide benefits for all parties, so that products in Islamic banking should be products that can provide services and can also increase economic growth, such as providing working capital financing. There are four possible approaches that can explain the causal relationship between finance and growth, namely:

a. The supply-leading hypothesis

This theory generally assumes that the financial sector drives economic growth. This theory is basically looking for the relationship between finance and economic development. Adherents of this theory believe that the existence of the financial sector which acts as an intermediary institution between those who are excess capital (surplus unit) and those who lack capital (deficit unit) will provide efficient allocation of funding sources that will drive economic sectors in the future, the growth process.

b. The demand-following hypothesis

The thinking developed by Robinson (1952) suggests that the development of the financial sector follows economic growth or entrepreneurial activity, which will encourage the growth of the financial sector. If the economic sector progresses, the demand for banking products and services will also increase, so that the banking sector will automatically increase as well.

c. The feedback hypothesis

This hypothesis describes a two-way relationship or mutual influence between the financial development sector and economic growth. This hypothesis states that a country with good financial sector development will encourage a high economic expansion level through technological advances and product and service innovation (Schumpeter, 1912).

d. The neutrality hypothesis

In contrast to the previous view, the neutrality hypothesis sees that there is no significant causal relationship between financial sector development and economic growth. The relationship between the two is neutral. In other words, financial sector development and economic growth are independent of each other (Lucas, 1988).

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2.2 Economic Growth

In Adam Smiths’s book entitled "An Inquiry into the Nature and Causes Wealth of Nation (1776)," Adam Smith argued that the process of economic growth was divided into two main aspects, namely total output growth and population growth. There are three main components in achieving the total output growth: natural resources, human resources, and available capital goods (Sukirno, 2006). Based on population growth, Adam Smith argues that the population will increase if the wage level exceeds the minimum wage. The growth rate in the capital stock and the growth in output determine the rate of growth in the demand for labor.

The theory of economic growth, according to Harrod-Domar, aims to explain the conditions that must be met to achieve economic growth in the long run (Sukirno, 2006). According to Jingan (2003), Harrod and Domar's investment played an important role in economic development. In theory, to grow economic growth, it requires capital formation as an additional stock of capital. Capital formation is considered an expenditure that can support the production of goods because it can foster effectiveness throughout society—the more investments that are carried out, the faster the economic growth (Todaro, 2006). Beside that supply and demand play an important role in determining the output of an economy. Therefore, the main component of the growth theory is the production function, which is the basis of supply, and the consumption function, which is based on demand.

2.3 Inflation

There are three kinds of theories that discuss inflation, namely quantity theory, Keynesian theory, and structuralist theory.

a. Quantity Theory

According to this theory, inflation occurs due to increased money supply and public expectations regarding future price increases. Even though there is an increase in price, it is not followed by the rise in the amount of money in circulation, and it cannot be said to be inflation. Inflation will only occur if the amount of money in circulation has increased. Meanwhile, regarding the effect of public expectations on price increases, there are three possibilities that can occur due to inflation, namely (1) when the public has not predicted a price increase that will happen in the future, (2) When the public starts to realize that inflation has occurred and estimates that there is an increase in prices in the future, (3) when there has been hyperinflation where people have started to lose confidence in the value of the currency. The increased velocity of circulation marked this situation.

b. Keynesian Theory

According to the Keynesian theory, inflation occurs because of the behavior of people who want to have a high level of desire that exceeds the limit of their economic capacity, so that people's demand for goods will exceed the amount available. People belonging to this group will endeavor to obtain additional funds beyond their financial ability to fulfill their wishes. This situation causes an inflationary gap. This seizure process is finally translating into a situation where the public's demand for goods always exceeds the number of goods available (Boediono, 1985).

c. Structuralist Theory

This theory discusses the rigidity of the economic structure when there is inflation in the long run that occurs in developing countries. According to structuralist theory, the rigidity or inelasticity that arises is due to import revenues and the rigidity of foodstuffs supply in developing countries. The result of this rigidity is an increase in other prices resulting in inflation.

3. Research methodology

Data used in this study are secondary data with time period from January 2004 – December 2019 obtained from various sources, namely Financial Services Authority, Bank Indonesia and World Bank. In processing the collected secondary data, the author uses several statistical tools, such as Microsoft Excel 2010 and E-views 9.0.

Microsoft Excel 2010 is used for data processing related to table creation and analysis, while E-views 9.0 is used for data processing. The analysis method used in this research is the Co-Integration Test and the Vector Error Correction Model (VECM) to see the relationship between three independent variables and the dependent variable in the short and long term.

The variables used in the research and their operational definitions are as follows:

a. Economic growth

Economic growth is one measure that can describe the standard of living. The economic growth variable used is Indonesia's annual economic growth as the measurement tool chosen in the public sector. The data used in this study are real GDP data from January 2004 – December 2019 period.

b. Islamic Financing

Islamic financing is one of the important instruments in developing Micro, Small & Medium Enterprises businesses carried out by entrepreneurs. Islamic financing is used based on the type of use and business

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category consisting of working capital, investment and consumption. In developing Micro, Small & Medium Enterprises businesses through Islamic financing, this will also trigger economic growth. The purpose of this Islamic financing variable is a description of the development of the halal industry in Indonesia. Variables are taken from the period of January 2004 – December 2019.

c. Inflation

In this study, the variables used in calculating the rate of inflation in food are the Consumer Price Index (CPI) with the base year 2010. CPI is a statistical data calculation of the average price of goods and services consumed by the public at large in a country. The inflation rate in the CPI is a fluctuation of changes from the previous year. Variables are taken from the period of January 2004 - December 2019.

d. Global Economic Growth

In this study, the global economic growth variable is a control variable in controlling the movement of the supply level. The variable used is real GDP from January 2004 - December 2019 period.

To make it easier to find out the data, it will be explained in the summary table of the following operational definitions:

Table 2. Operational Variables

No. Abbreviation Variable Unit Source

1. LNISFN Islamic Financing Percent (%) Otoritas Jasa

Keuangan 2. INF Inflation Inflation Rate = !"#$%!"#$%&

!"#$%& x 100%

Percent (%)

Bank Indonesia

3. GDPI Gross Domestic Product

Indonesia 𝐺𝐷𝑃_$%'()*$+= ,-.$%,-.$%&

,-.$%& x 100%

Percent (%)

World Bank

4. GDPW Gross Domestic Product

World 𝐺𝐷𝑃_$%'()*$+= ,-.$%,-.$%&

,-.$%& x 100%

Percent (%)

World Bank

4. Result and Analysis 4.1 Empirical Results a. Unit Root Test

This test uses Eviews-9, in the guide, if the ADF t-statistic is smaller than the alpha value of 5% (0.05), then H0 is rejected, H1 is accepted, which means it does not contain a unit root and the data is stationary.

Table 3. Unit Root Test-Level Method

Level

T-stat Prob Note

Levin, Lin & Chu -2.42527 0.0076 Stationary

Im, Pesaran & Shin -2.33391 0.0098 Stationary

ADF 17.8839 0.0221 Stationary

PP 31.9832 0.0001 Stationary

Source: Data Processed

Based on table 3, it can be seen that all variables used in this study through 4 methods, namely Levin, Lin &

Chu, Im, Pesar & Shin W-stat, ADF, and PP are stationary at the level, where the probability value of each method is less than 5 % which means that H0 is rejected. H1 is accepted, which means the data is stationary.

b. Lag Length Criteria

After performing the unit root test, the next step will be a lag length test. The optimum lag test is needed to reduce autocorrelation in the VAR model. The optimal lag testing on the VAR model will be recommended using the Final Prediction Error (FPE), Akaike Information Criterion (AIC), Schwarz Criterion (SC), and Hannan-Quin (HQ). Optimization occurs when a certain lag has the most stars sign.

Table 4. Lag Length Criteria

Lag LogL LR FPE AIC SC HQ

0 283.0744 NA 0.000237 3.006015 3.074126 3.033603

1 1384.230 3247.316* 7.35e-12* -14.28513* -13.94458* -14.14719*

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Based on table 4, the researcher chose lag 1, and there was the most stars sign, which means that lag 1 passed each test, so this lag was also selected as the optimal lag based on the criteria. Thus, it can be ascertained that the optimal lag used in this study is lag 1 because it is free from white noise and has fulfilled the classical assumption test.

c. StabilityVAR Model Test

In the stability of the VAR estimation test, the root characteristic of the polynomial will be tested. The VAR system is said to be stable if all roots have a modulus of less than 1. In the table below, the VAR model is stable at its optimum lag, namely 1. So, the VAR estimation to be estimated for IRF and FEVD analysis is valid.

Table 5. Test of VAR Stability

Root Modulus

0.992673 0.992673

0.969528 0.969528

0.939572 – 0.067543i 0.941997

0.939572 + 0.067543i 0.941997

d. Co-Integration Test

The determination of cointegration can be seen from the trace value and max-eigen statistics. When the trace and max-eigen statistics are higher than the critical value (5%), this indicates a cointegration in the model. If in this test, there is no cointegration, it is recommended to use the VAR (Vector Autoregression) method.

Table 6. Co-Integration Test Hypothesized No. of

CE (s)

Eigenvalue Trace Statistic

0.05 Critical Value

Prob^**

None * 0.408830 131.6803 47.85613 0.0000

At most 1* 0.084860 31.80639 29.79707 0.0290

At most 2 0.046805 14.95746 15.49471 0.0601

At most 3 * 0.030319 5.849753 3.841466 0.0156

Hypothesized No. of CE (s)

Eigenvalue Max-Eigen Statistic

0.05 Critical Value

Prob^**

None * 0.408830 99.87394 27.58434 0.0000

At most 1 0.084860 16.84894 21.13162 0.1792

At most 2 0.046805 9.107704 14.26460 0.2773

At most 3 * 0.030319 5.849753 3.841466 0.0156

Based on table 6, it can be seen that the trace statistical value and the maximum eigenvalue at r = 0 are higher than the critical value with a significant level of 5%. It shows H0, which states that no cointegration is rejected, and H1, which states that there is cointegration accepted. In conclusion, the study results indicate that the movement of all variables has a relationship between stability and a long-term relationship. In other words, in any short-term relationship, all the variables also adjust in the long-term.

e. Granger’s Causality Test

This test is conducted to determine and prove the direction of the short-term relationship between variables and the reciprocal relationship between variables.

Table 7. Pairwise Granger Causality Tests

Null Hypothesis Obs F-Statistic Prob.

GDPI does not Granger Cause LNISFN 191 3.16389 0.0769

LNISFN does not Granger Cause GDPI 9.67625 0.0022

GDPW does not Granger Cause LNISFN 191 2.97762 0.0861

LNISFN does not Granger Cause GDPW 0.00560 0.9404

INF does not Granger Cause LNISFN 191 10.7293 0.0013

LNISFN does not Granger Cause INF 4.32210 0.0390

GDPW does not Granger Cause GDPI 191 6.49143 0.0116

GDPI does not Granger Cause GDPW 3.20159 0.0752

INF does not Granger Cause GDPI 191 8.07386 0.0050

GDPI does not Granger Cause INF 5.12647 0.0247

INF does not Granger Cause GDPW 191 4.66985 0.0320

GDPW does not Granger Cause INF 4.21706 0.0414

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Table 7 shows that those who have a causal relationship have a probability value smaller than α 0.05 so that H0 will be rejected, which means that a variable will affect other variables. In the table above, the following results are obtained:

1. GDPI variable does not significantly affect LNISFN variable with a probability value of 0.0769 so that it accepts H0, while LNISFN variable significantly affects GDPI variable with a probability value of 0.0022 so it rejects H0. It can be concluded that there is a unidirectional causality between GDPI and LNISFN variables.

2. GDPW variable does not significantly affect LNISFN variable with a probability value of 0.0861 so that it accepts H0, while LNISFN variable does not significantly affect GDPW variable with a probability value of 0.9404 so it accepts H0. It can be concluded that there is no one-way or two-way causality between GDPW and LNISFN variables.

3. INF variable significantly affects LNISFN variable with a probability value of 0.0013 so that it rejects H0, while the LNISFN variable significantly affects the INF variable with a probability value of 0.0390 so it rejects H0. It can be concluded that there is a two-way causality between the INF and LNISFN variables.

4. GDPW variable significantly affects GDPI variable with a probability value of 0.0116 so it rejects H0, while GDPI variable does not significantly affect GDPW variable with a probability value of 0.0752 so it accepts H0. It can be concluded that there is a unidirectional causality between GDPW and GDPI variables.

5. INF variable significantly affects GDPI variable with a probability value of 0.0050 so it rejects H0, while GDPI variable significantly affects INF variable with a probability value of 0.0247 so it rejects H0. It can be concluded that there is a two-way causality between INF and GDPI variables.

6. INF variable significantly affects GDPW variable with a probability value of 0.0320 so it rejects H0, while GDPW variable significantly affects INF variable with a probability value of 0.0414 so it rejects H0. It can be concluded that there is a bidirectional causality between INF and GDPW variables.

f. Vector Error Correction Model Estimation

After carrying out several steps, namely the data stationarity test, the determination of the lag length, cointegration test, and VECM stability and the fact that there are three cointegration ranks at the 0.05 level in this study, the model to be used is VECM (Vector Error Correction Model). The results of data processing at VECM will get a short and long term relationship between the dependent variable (LNISFN) and the variable (INF, GDPI, GDPW). In this study using lag 1 based on the lag length criteria. The table below shows the short-term and long- term relationship between Islamic Financing (LNISFN) as the dependent variable and other variables as independent variables; here are the results:

Table 8. VECM Model in Short Term

Short Term

Variable Coefficient T-Statistic

CointEq1 -0.008885 [-5.83432]

D(LNISFN(-1)) 0.214198 [ 3.15465]

D(GDPI(-1)) -0.290864 [-1.09875]

D(GDPW(-1)) 0.023062 [0.28636]

D(INF(-1)) 0.000389 [0.31216]

From table 8, it can be explained that in a short-term relationship, inflation at lag 1 has a positive effect of 0.000389. It means that if there is an increase in inflation in the previous month, it will increase the Islamic Financing assets by 0.000389 units.

The next significant variable is world economic growth at lag 1, which has a positive effect of 0.023062. It explains that the increase in world economic growth in the previous month will increase Islamic Financing assets by 0.023062 units.

The last variable is Indonesia's economic growth at lag 1, which has a negative effect around 0.290864. It explains that the increase in Indonesia's economic growth in the previous month will reduce Islamic Financing assets by 0.290864 units.

Table 9. VECM Model Factors Influencing LNISFN in Long Term Long Term

Variable Coefficient T-Statistic

GDPI (-1) 5.442951 [2.77337]

GDPW (-1) -4.585316 [-6.02290]

INF (-1) 0.289557 [11.7126]

Meanwhile, in the long-term estimation, the GDPI variable has a positive impact on Islamic Financing (LNISFN), which is 5.442951 percent. It means that if there is an increase in Indonesia's national income (GDPI), it will cause Islamic Financing (growth of the halal industry) to increase by 5.442951 percent in the long-term.

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The inflation variable (INF) also has a positive impact on Islamic Financing (LNISFN), which is 0.289557 percent. It means that if there is an increase in inflation (INF), it will cause Islamic Financing Financing (growth of the halal industry) to increase by 0.289557 percent in the long-term.

The world national income variable (GDPW) has a negative impact on the development of the halal industry in Indonesia, amounting to 4.585316 percent. It means that any increase in the development of world national income will reduce the development of halal in Indonesia by 4.585316 percent in the long-term.

g. Impulse Response Function (IRF)

Impulse Response Function can provide an overview of the response of a variable in the future to disturbances or shocks to other variables. Thus, the duration of the effect of a shock or variable on other variables until the effect is lost or returns to the equilibrium point can be seen from here. This test shows how long it takes for one variable to respond to a shock to another. The IRF (Impulse Response Function) analysis is as follows:

1. LNISFN Response on GDPI

The first IRF analysis is determined to explain LNISFN (Islamic Financing) based on constant prices, namely, the response of LNISFN to GDPI (Indonesia's Gross Domestic Product) in Indonesia. The responses given by LNISFN to GDPI in 10 periods are as follows.

Figure 1. Response of LNISFN to GDPI

Figure 1 shows that the response of LNISFN (Islamic Financing) to the shock variable GDPI (Indonesia's Gross Domestic Product) experienced a positive response. However, in the second, third and fourth periods of GDPI shocks responded negatively. From the fifth period to the tenth period, the response returned to normal.

2. LNISFN Response on GDPW

The second IRF analysis is determined to explain LNISFN (Islamic Financing) based on constant prices, namely, the response of LNISFN to GDPW (Gross Domestic Product World). The responses given by LNISFN to GDPI in 10 periods are as follows.

Figure 2. Response of LNISFN to GDPW

Figure 2 shows that LNISFN began to respond to GDPW from the first period. On the other hand, the response tended to decrease from the third to the eighth period and increased again in the ninth and tenth periods.

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3. LNISFN Response on INF

The third IRF analysis is determined to explain LNISFN (Islamic Financing) based on constant prices, namely, the response of LNISFN to INF (inflation). The responses given by LNISFN to GDPI in 10 periods are as follows.

Figure 3. Response of LNISFN to INF

Figure 3 shows that LNISFN started to give negative responses to INF from the first period. From the first to the tenth period, the response was quite stable. The graph explains that the increase in inflation is pressing the halal sector.

h. Variance Decomposition

VDC (Variance Decomposition) analysis aims to measure the amount of composition or contribution of the independent variable's influence on the dependent variable. In this study, the VDC analysis focused on the effect of the independent variable (GDPI, GDPW, INF) on the dependent variable, namely LNISFN. The results of the VDC analysis are as follows:

1. LNISFN (Islamic Financing)

The LNISFN VDC analysis results explain how much contribution to form the LNISFN variable from each variable. The following will explain the contribution of variables from period 1 to period 10, as follows:

Table 10. The Result of VDC

Variance Decomposition of LNISFN

Period S.E. LNISFN GDPI GDPW INF

1 0.018299 100.0000 0.000000 0.000000 0.000000

2 0.028882 99.14751 0.212331 0.041226 0.598935

3 0.037461 97.27004 0.183052 0.032877 2.514030

4 0.045093 94.41525 0.126424 0.024719 5.433611

5 0.052278 90.89776 0.121779 0.019322 8.961139

6 0.059257 87.03870 0.181522 0.015744 12.76404

7 0.066143 83.08958 0.294749 0.013293 16.60238

8 0.072983 79.22160 0.445434 0.011563 20.32140

9 0.079798 75.53881 0.619012 0.010310 23.83187

10 0.086587 72.09642 0.804136 0.009383 27.09006

Table 10 above explains the results of the Variance Decomposition of the LNISFN variable and how much other variables contribute to the LNISFN variable. In the first period, the LNISFN variable was influenced by the LNISFN variable itself, which was 100%. The other variables are as follows:

a) GDPI (Gross Domestic Product of Indonesia) in the second period contributed 0.21% and fluctuated until the fifth period by 0.12%. In the sixth period, the variables contributed again and increased until the tenth period was 0.80%. It means that these variables do not fully contribute to the halal industry’s development throughout the period.

b) GDPW (Gross Domestic Product World) in the second period contributed 0.041% and fluctuated until the tenth period of 0.009%. It means that these variables do not make a big contribution to the halal industry’s development throughout the period.

c) INF (Inflation) in the second period contributed 0.59% and increased in each period up to the tenth period, INF contributed 27.09%. It means that the inflation variable contributes to the halal industry’s development.

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4.2 Analysis

a. Granger’s Causality Analysis

From the Granger causality analysis results, Indonesia's economic growth is directly related to the development of the halal industry. The hypothesis that can explain the above statement is the demand-following hypothesis. When the economic sector increases, the demand for banking products and services will also increase, so that the growth of the financial sector will automatically increase. Research that supports this hypothesis, namely Habibullah (2006) in his research in seven Asian countries, found that Malaysia, Myanmar, and Nepal supported the "growth-led finance" hypothesis, and only the Philippines supported the "finance-led growth"

hypothesis.

Inflation has a bidirectional relationship with the halal industry’s development, so the hypothesis related to this is the feedback hypothesis. This hypothesis states that inflation is a condition in which there is excess demand for goods in the economy (Lunher in Utomo, 2006). This condition will create a high level of demand for banking products and services (Levine, 1997). If banking institutions respond effectively to these requests, then this response will stimulate higher economic performance and support the growth of the halal industry. So that the level of people's purchasing power is considered in the development of the halal industry.

There is no relationship between world economic growth and the halal industry’s development, so the hypothesis related to this is the neutral hypothesis. This hypothesis states that the halal industry’s development sector in Indonesia is still underdeveloped, so it takes efforts to develop its functions effectively. It is contrary to the supply-leading hypothesis and demand-following hypothesis, which explains that the financial sector has a relationship to economic growth. The research that is in line with this, namely research by Al-Zubi, et al. (2006), where the results of the research show that all financial indicators are not significant and have no effect on economic growth.

b. VECM in Short Term

In the short term, the estimation results show that inflation affects the development of the halal industry with a positive relationship of 0.000389. This positive relationship occurs because of the high level of public demand (purchasing power) for halal products based on the quantity theory which explains the occurrence of inflation caused by the high demand for a good or service and society’s expectations of future price increases. In other words, the society is aware of an increase in prices with each increase in the consumption of halal products so that the inflation rate has a positive impact on the development of the halal industry.

Another important variable in short-term estimation is Indonesia's economic growth. This variable has a negative relationship with the halal industry’s development with a value of -0.290864. It happens because the development of the halal industry in Indonesia has not become a trend, so that Indonesia's economic growth has not been able to encourage the development of the halal industry in the short-term. It is in line with Farhani and Dastan (2013) research, which states that the relationship between economic growth and the development of the halal industry is still very weak in the short term.

As for the world economic growth variable in the short-term, it affects the halal industry’s development by 0.023062. It happens because the development of the halal industry has become a trend in the world. According to the Halal Industry Development Cooperation (HDC), it is clear that halal products are currently the main value of the supply chain in various industrial sectors as well as halal products have great potential to develop the financial sector both globally and domestically from the real sector.

c. VECM in Long Term

In the long-term, the variable of economic growth in Indonesia and the variable of inflation have an impact on the development of the halal industry with coefficients of 5.442951 and 0.289557 respectively.

Indonesia's economic growth has a positive impact on the development of the halal industry. This positive relationship occurs because economic growth in Indonesia encourages the development of the halal industry and becomes a trend for people in Indonesia in the long-term. It is in line with the feedback hypothesis which explains the relationship between the financial sector and economic growth. This variable is also proven by researchers Furqani and Mulyany (2009), stating that any increase in GDP can cause Islamic banking to develop in the long- term.

In line with the research conducted by Abduh and Azmi Omar (2010), it is stated that there is a significant relationship in the short and long term between the development of Islamic finance and economic growth. As well as reinforced by research by Zirek, Celebi, and Hassan (2016) stated that there is a significant positive relationship to Islamic finance and economic growth in the long-term.

Inflation has a positive impact on the development of the halal industry in the long-term. This positive relationship occurs because the government can elaborate and consider inflation (purchasing power) as an indicator of increasing the development of the halal industry in Indonesia in the long-term. Researchers Andres, Hernando, and Salido (2002) also state that inflation affects economic growth through financial markets

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interactions. In line with Nurdin (2017) research, which states that inflation has a positive influence on the development of the halal industry.

And finally, world economic growth has a negative impact on the development of the halal industry in the long-term. This negative relationship occurs because the development of ecosystems in Indonesia is still not well developed. As well as a shift in the world's sharia economy, which initially encouraged the development of the halal industry in the financial sector and now the focus is on the real sector. So that there is no strong integration carried out by the Indonesian government to create the benefit of the people for the development of the halal industry.

d. IRF Analysis

IRF shows the response to changes from one variable to another. In this study, the IRF graph varies from one variable to another. The following is an explanation of each variable.

For the variables of Indonesia's economic growth and world economic growth, a positive relationship in the short-term triggers the development of Islamic Financing in the growth of the halal industry. It is in line with the demand-following hypothesis put forward by Robinson (1952), which states that the development of the financial sector follows economic growth. Which is if the economic sector has increased, then the development of the financial sector will also increase.

In this graph, the development of the halal industry gives a negative response to inflation. It proves that the development of the halal industry is still very sensitive to shocks caused by inflation. For Islamic banking, this can trigger a level of financing risk so that the higher the inflation, the distribution of financing will decrease. It is in line with Dahlan's (2014) statement that there is a negative influence between inflation and Islamic Financing.

e. FEVD Analysis

The summary results of the FEVD as the dependent variable of LNISFN show that the inflation variable is a variable that makes a significant contribution to the development of the halal industry in Indonesia. The contribution to inflation of 27.09% was followed by Indonesia's economic growth of 0.8% and world economic growth of 0.009%.

Based on the analysis, inflation is the variable that most contributes to the development of the halal industry.

It happens because inflation (purchasing power) is considered as the level of people's purchasing power that increases in demand for halal products to support the growth of the halal industry in Indonesia. As for the impact of the increase in inflation, the government must make the right decision in maintaining the strength of the rupiah so as not to disrupt Indonesia's economic growth. In other words, the high contribution of inflation to the halal industry in Indonesia must be accompanied by government action in regulating the balance to not affect the income earned.

5. Conclusion and recommendation

This research aims to analyze factors that affecting the halal industry development in Indonesia in the short term and long term. Based on findings in this research, it can be concluded several things about the factors that affecting the halal industry development in Indonesia.

In short term, inflation has a significant and positive impact on the halal industry’s development in Indonesia in the short-term. It means that there is a level of awareness of the Indonesian people in consuming halal products to encourage the halal industry's development and make the halal industry a trend or lifestyle in Indonesia.

Indonesia's economic growth has a negative impact on the development of the halal industry in Indonesia because the halal industry in Indonesia has not yet become a lifestyle trend. That is why Indonesia's economic growth has not been able to encourage the halal industry's development. The world economic growth has a significant impact on the halal industry’s development because the world’s halal industry has its own halal lifestyle trend, thus encouraging the growth of the halal industry in Indonesia.

In the long term, inflation has a significant impact on the development of the halal industry in Indonesia in the long-term. It happens because of the Indonesian people's awareness as Muslims in consuming halal products to encourage the development of the halal industry and make the halal industry a trend of halal lifestyle in Indonesia.

Beside that, the government can elaborate and consider inflation (purchasing power) as an indicator of increasing the development of the halal industry in Indonesia in the long-term. Indonesia's economic growth has a significant impact on the development of the halal industry in Indonesia in the long-term. It happens because of an increase in Indonesia's economic growth to encourage the growth of the halal industry in Indonesia. World economic growth has a negative impact on the development of the halal industry. It happens because there is no strong integration between the Indonesian government and outsiders in developing the halal industry. And the world's halal industry has its own trend that focuses on the real sector.

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In other words, the Indonesian people take a bottom-up approach in increasing the development of halal industry itself. The development of halal industry in Indonesia still depends on the society and need the encouragement from the government in developing halal industry in Indonesia.

Based on the result of the research, there are some recommendation for government to develop halal industry in Indonesia:

1. The inflation rate has a significant impact on the growth of the halal industry in Indonesia. The government, as the decision-maker in monetary policy, can stabilize excess inflation fluctuation.

2. National income in Indonesia has a significant impact on the growth of the halal industry in Indonesia. The government should motivate society to raise awareness in using halal products in Indonesia.

3. World national income does not show a significant impact on the growth of the halal industry in Indonesia. It needs the role of the government that should work together with society and outsiders in developing the halal industry.

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