More than five million workers have lost formal sector jobs because of lockdowns, which forced many businesses to close. Their incomes were cut in half or were lost entirely. Another two million workers joined the labor force. These seven million face a miserable existence because of the coronavirus and the resulting economic slowdown.

For moral, economic, and political reasons the government should soften the blow suffered by the poor. But government revenues declined and for decades the deficit has been limited to three percent of gross domestic product.

A major reason for limiting the deficit is the fear of inflation. But the steps to control the virus have caused a recession. The problem is lack of demand, not excess demand. An increase in demand would bring about an increase in supply, not price inflation.

In addition, our model shows that the lockdown has resulted in “forced savings,” something not considered in other models. Many people are confined to their homes. They cannot spend as much as usual dining out, going to movies, traveling, or even commuting to work. Entrepreneurs and government cannot carry out their investment plans. This income is saved, resulting in a decline in demand, while creating a pool of resources that can finance higher government deficits.

A third source of deficit finance is the growth of government revenue derived from the increase in GDP that the subsidy will generate. Families receiving government support will spend most of it on food and other necessities. That will increase incomes of those that produce and trade these goods. They in turn spend money on goods and services, generating further rounds of income. We estimate these indirect, or multiplier, effects of government spending at 1.6 to 1.8 times the original expenditure. The government collects taxes on this additional economic activity.

With a 10 percent subsidy the deficit reaches 15 percent. But it is more than offset by savings of 18 percent so there is no increase in inflation. Indeed, our model indicates that government deficit financing can reach 23 percent before inflationary pressures emerge and the balance of payments turns negative. With a 10 percent subsidy GDP will be nearly 15 percent higher than with no subsidy.  Consumption will improve even more, increasing 7.4 percent with the subsidy but falling 22.7 percent without it.

Indonesia´s GDP is approximately US$1 trillion per year, or $250 billion per quarter. We estimate that 140 million citizens are poor or in need of help, a reasonable assumption given the collapse of the hospitality industry, the decline of exports and the general recession of the economy. At a 10 percent subsidy, each person in need of assistance could receive $1.94 per day in current US dollar.

A 10 percent subsidy would be fully financed out of forced savings caused by the lockdown together with the rise in GDP brought about by the subsidy itself. Our model also shows that this would occur while still increasing the level of international reserves.

Millions of people lost their jobs nine months ago. It is imperative that the subsidy be disbursed as quickly as possible. Fintech provides the means to achieve this. There are over 193 million cellphones in Indonesia, virtually one for every adult. All can receive money. The fastest way of delivering the subsidy is for the government to open a digital bank account at Bank Rakyat Indonesia for all cellphone owners. Then the government can deposit the subsidy into these digital bank accounts at negligible cost and with minimal delay. With most Indonesians having cellphones, they could make payments to each other, without needing many cash-out points.

Technology can be used to determine where cellphones “sleep” by making use of cellphone: tower use data collected by telecom companies. This information could be used to match cellphone owners to their actual addresses even if the registered owner of the cellphone lives somewhere else.

The subsidy could therefore be targeted to cellphone users residing in areas where many poor people live. Then a small subsidy, say four days’ worth, would be sent to these. To receive further payment, recipients would be required to enter their ID card number into the phone to prevent duplicate payments. To prevent ID theft, additional information, known only to the holder of the ID, would be required, such as the date of birth and ID date of issue. The government would need to launch an urgent program to issue ID cards to the many poor who do not have them.

The typical family with two adults owning cell phones and two dependents would receive roughly $240 a month, well above the Indonesian government’s poverty line of $150 per family month. This would be a temporary measure, for1-3 quarters. Many families will be heavily indebted by now.

The extra funds will enable them to reduce their debts and rebuild such assets as a bag of rice. Refinements can be made to the use of artificial intelligence described above, such as frequency and hour of use, connection to towers in low-income areas, and correlation with past information on the poor, including data from household surveys. Even so, some of the poor will not get the subsidy and some non-poor will receive it. However, the great administrative and speed advantages of applying fintech and big data more than compensate for these targeting errors.

Indonesia has the resources needed to help the poor through this difficult time and the means to deliver it. Everyone, even the non-poor, would benefit from faster economic growth. The time to act is now.

***

The writer is a professor emeritus of economics at Boston University and the president of Boston Institute for Developing Economies (BIDE).

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