The role of inter-household transfers in mitigating the impact of economic shocks on income distribution in Indonesia

1.Introduction

The dynamic movement of the global economy often creates shocks for the national economy. The impacts carried by those external shocks vary from mild to severe. One of the external shocks that is currently taking place and bringing big impacts ubiquitously is COVID-19 pandemic.

The outbreak that began in Wuhan City, Hubei Province, China in December 2019, at the beginning of the incident had a major influence on China and its partner economies and impacted on the decrease of global trade, global demand and output, and world commodity prices. At the next stage, COVID-19 also rapidly affected wider economies, including Indonesia.

First COVID-19 case detected in Indonesia in early March 2020, contracted by two residents living in Depok, a satellite city south of Jakarta. Not long after that, the number of residents which were positively infected increased rapidly. According to official data from the government, as of June 29, 2020, there were 55,092 people positively infected, 23,800 patients recovered, and 2,805 dead. Those cases were spread in 34 provinces and 496 municipalities/cities [1]. By considering the virus high transmissibility and unavailability of the vaccines and relevant medicine, the government implemented physical distancing as a preventive measure to slow down the virus spread.

This measure brings decelerating impacts on economic aspects, ranging from activities of production and distribution, consumption, investment, and international trade, to income. Physical distancing reduces business capacity to invest and operate, hampers capacity of households to consume goods and services, and holds back residents’ transactions with foreign counterparts which leads to lower institutions’ income.

As an effort to cope with the impact of the coronavirus outbreak, the government issued fiscal stimulus policies by refocusing the government budget to be more accommodating the needs for health and social assistance. Besides, income taxes were loosened and transfers to households and the business sectors were increased to maintain the consumption [2].

In line with the government efforts, other institutions such as businesses, non-profit institutions, and households also take part in the efforts by raising funds and donating aid in the form of cash, food, medical supplies, etc. to hospitals, medical teams, security personnel and related workers and as well as community members in need.

In this regard, this paper attempts to discuss the potential impacts of various economic shocks caused by COVID-19, which consists of decreased world commodity prices, physical distancing, government stimulus package, and increased inter-household transfers on Indonesian economy. The discussion will emphasize on the impact of inter-households transfer on income distribution, by considering that research in this topic is relatively scarce, despite the long history of the role of inter-households transfers in society.

2.Literature review

Impact of pandemic on the economy topics have been investigated by researchers by using various analysis tools. Chen et al. [3, pp. 281–293] studied the impact of SARS outbreak on Taiwan stock market during the outbreak period in 2003 by applying the GARCH method. Hussain et al. [4, pp. 585–589] analyzed the potential cost of food safety outbreak in the United States utilizing some examples of outbreak. Macciocchi et al. [5, pp. 287–289] analyzed short-term impact of Zika virus outbreak on Latin American and Caribbean countries (LCR) markets using variations of the market index and linear regression model. Hossain et al. [6, pp. 585–589] conducted cross-sectional study of chikungunya outbreak in Bangladesh by using multivariate analysis based on clinical and socio-economic patient data. Dewi et al. [7, pp. 77–85] estimated total economic losses caused by Surra outbreak in Sumba Timur-Indonesia by calculating direct cost, indirect cost, and the other expenditure cost based on primary and secondary data.

Those research in general discussed the impact of outbreaks on specific aspects of the economy. Other research studied the impact on wider economic aspects by utilizing computable general equilibrium (CGE) models. Diao et al. [8, pp.145–158] assessed the potential economy wide impact of HPAI outbreak using the dynamic CGE model for Nigeria. Thurlow [9, pp. 276–288] analyzed avian flu impact on economic growth and poverty using dynamic CGE model of Kenya. The research indicate that supply and demand shocks caused by avian influenza affect income from poultry production significantly and increase the risk of poverty for poultry farmers. However, the effects of the outbreaks on economic growth are limited, since poultry shares to the economies are relatively small. Smith et al. [10, pp. 1400–1408] estimated the potential macroeconomic impact of influenza pandemic (H1N1) in Thailand, South Africa and Uganda using comparative static single-country CGE models. The research indicates that effect of influenza outbreaks on labor-intensive sectors is large, but in overall the effect of the outbreaks on the economies are relatively small. Prager et al. [11, pp. 1–19] analyzed the total economic consequence of potential influenza outbreak in the United States by utilizing the static CGE model for the US. The research highlights the importance of vaccination and other actionable activities could be done by the stakeholders to reduce potential economic losses from the outbreaks. Very recently, Center for Sustainable Development Goals Studies [12] measured the real economic cost of COVID-19 pandemic in Indonesia using inter-regional CGE model entitled IndoTERM, combined with simple cost benefit analysis. The analysis concluded that strong intervention through effective large-scale social restrictions could reduce economic growth in the short run but could lead to higher economic growth than the weak intervention in the long run.

3.Methodology

Learning from previous research and aligning with the research objectives, this study uses the CGE model to estimate impacts of various shocks which were mainly caused and triggered by COVID-19 on Indonesian economy. The use of CGE model in this research is based on consideration that the model could cover many economic issues and integrate microeconomic and macroeconomic perspectives, and has the capability to formulate it well. CGE model also did not require up-to-date, long, and consistent series data which are commonly unavailable in developing countries, including Indonesia [13]. The model is combination of economic theories and economic data which formulated in large numerical equations to measure the impacts of policies or shocks in the economy [14].

However, despite those advantages, CGE model shares the feature of a deterministic model, which does not fully cover all economic circumstances in depicting the phenomena. Besides, CGE models are quantitative yet theoretical and not empirical in the sense of econometric modeling [15].

The model used in this study is the development of the previous model used to study the impact of inter-households transfers on the economy in Indonesia [16, pp. 1–12], which is a modified version of the original model introduced by Hosoe et al. [17]. The model is static and classified as a neoclassical class model that describes analysis of long-term impacts. The model assumed that Indonesia is a small country in the global competition, all markets in the economy are at perfect competition condition, production process tends to have constant return to scale, and endowment factors in the economy are fixed, immobile and work at full capacities.

The model is homogeneous of degree zero in prices that achieve balance condition by adjustments in commodity and production factor prices and exchange rate. Total income of each row in the SAM data is equal to its total column and total of GDP by production is equal to total of GDP by expenditure in current prices. In overall, the model consists of 40 blocks of equation and variables with 4,603 single equations and variables. The model solution is carried out by maximizing the sum of household Hicksian equivalent variation using non-linear model.

The main data used in this study is the 2015 Indonesian social accounting matrix (SAM) which is the updated data of official 2008 Indonesian SAM, the latest edition of official data that is available up to now. SAM is one of satellite accounts that record interplay between social and economic aspects of the compiling economy and is very widely used as a database of CGE models. An update of the SAM is needed to describe a more current structure of the Indonesian economy in order to be able to depict current Indonesia’s economic characteristics which is quite different from 2008 period due to changes such as production technology and subsidy allocation that have impacted government saving and the current account balance.

The updated 2015 SAM consists of 55 accounts of production activities, 2 accounts of production factors (labor and capital), 2 accounts of net direct taxes and net import tariffs, 1 capital account, and 11 institutional accounts (8 household accounts, 1 corporation account, 1 government account, and 1 rest of the world account). In the updated SAM, the inter-household submatrix describes the inter-household transfers between the household groups in the household account. This household sub matrix describes something for nothing transactions between households, which means that one household intentionally gives cash, goods or services to the other but does not expect and receive a reward or return as a feedback.

In order to estimate the impact of the various shocks, this study simulates six scenarios as presented in Table 1.

Those simulations are designed to approximate the real economic phenomena as close as possible based on acquired information. However, due to dynamic circumstances, the information could be changed quickly, particularly that related to fiscal stimulus policy. In this context, the study uses the fiscal stimulus information as of June 16, 2020 [2].

4.Results and discussion

5.Conclusions

Commodity prices and physical distancing shocks caused by COVID-19 have adverse impacts on Indonesian economy, i.e. a decrease in production of goods and services, a decrease in consumption, investment, and international trade, a decrease in institutions’ income and saving, and an increase of current account deficit. The estimates also show that the largest adverse impact is caused by the physical distancing measure. physical distancing measures. Currently, physical distancing is one of the recommended measures in facing this contagious invisible enemy by hindering the virus contracting capacity. Nevertheless, from economic point of view physical distancing is not a sustainable solution since it limits the economy to work at its normal capacity.

Government response by reducing direct taxes and increasing transfers to households and corporations could not fully compensate for the adverse impacts, but could help to reduce it slightly. Hereinafter, households response by increasing inter-household transfer rates helps government policy in mitigating the impacts, particularly in the reduction of household income and consumption as well as corporation and government income.

When institutions have obstacle in generating income from the production activities, the distribution activity through transfers could be an alternative solution to maintain the economic flows. In this regard, collaboration of government authority in fiscal policy and society concern on inter-household transfer could be an effective asset in reducing the negative impacts and minimize the economic cost of COVID-19.

Accordingly, all stakeholders should strengthen the cooperation to improve the social solidarity and responsibility and capitalize it in order to be able to overcome the pandemic impacts and face other challenges in the economy.

From a statistical perspective, COVID-19 reveals the need for the accessibility and availability of up-to-date data to support studies, policies, and decisions making. Related to this study, availability of the up-to-date official data could improve reliability and accuracy of the simulation results.