VoxEU Column COVID-19 Labour Markets Macroeconomic policy

The coronavirus stimulus package: Quantifying the transfer multiplier

Among the various measures announced in response to the economic fallout caused by the COVID-19 pandemic, the $2 trillion stimulus package legislated in the US at the end of March 2020 stands out in terms of size. This column quantifies the multiplier of the stimulus’s transfer component. It finds that transfers which top up unemployment benefits are particularly effective because they reduce the income risk due to the lockdown ex ante. In this case, the multiplier may be as high as 2.

The economic fallout of the COVID-19 pandemic is unprecedented and widely discussed. The same holds for the response of economic policy to the crisis. In fact, policy makers have put in place a variety of measures rather speedily. And while actual measures are perhaps not as radical as some proposals (e.g. Bénassy-Quéré et al. 2020, Gali 2020), they are certainly impressive in terms of size and scope.

The CARES act: the largest stimulus ever

One of the measures without historical precedent is the ‘Coronavirus Aid, Relief, and Economic Security (CARES) Act’, signed into law by President Trump on 27 March 2020. As a result, $2 trillion of federal funds are being disbursed to households and firms through various channels. To put this into perspective, recall that the American Recovery and Reinvestment Act, legislated in 2009 in response to the financial crisis, mobilized only $800 billion of additional federal spending.

Under the CARES act, any adult in the US population with a gross income of $75,000 or less receives a one-time payment of $1,200. In addition, it includes a top-up to state unemployment benefits of $600 per week. Conditional on being unemployed, this top-up payment is lump sum and may run up to the end of July 2020. Each of these items is expected to amount to some $250 billion of federal expenditures.

These measures provide some relief for the individuals that are hit hard by the crisis, but they are also bound to have a macroeconomic impact. In a new paper, we quantify the multiplier effect of these transfer payments, i.e. the dollar change of the US GDP per dollar spent on transfers (Bayer et al. 2020a). We perform the analysis in a model of the HANK type, estimated on US data in earlier work (Bayer et al. 2020b). It features heterogenous agents (HA) in an otherwise conventional medium-sized New Keynesian (NK) model. The model is uniquely suited for our analysis of the transfer multiplier, because it accounts for both, possibly different labor market outcomes across households as well as the frictions that are necessary for a full-fledged business cycle analysis.

The lockdown generates income risk and major recession

We show that to compute the transfer multiplier correctly it is essential to account for the conditions under which the transfer takes place. For this purpose, we develop a baseline scenario in the first step of our analysis. Specifically, we assume that 10% of the labor force is confined to quarantine or, more generally, locked out of work. This implies a dramatic increase in unemployment by historical standards, even though it is still somewhat conservative in light of actual developments and current projections. From the aggregate perspective, this quarantine shock, or ‘Q-shock’ for short, boils down to a massive reduction of the labor force. From the household perspective it amounts to an exceptional increase of income risk because we assume that the lockdown is largely anticipated. People see it coming and have time to adjust their behavior in advance.

Figure 1 Adjustment to lockdown with and without transfer payments

Note: (‘Q-shock’) in black (baseline) and adjustment with transfer payments under CARES act (blue diamonds). Horizonal axis measures time in quarters, vertical axis percentage deviation from pre-shock level.

This is important for how the economy adjusts to the shock, shown in Figure 1 above. Output, shown in the left panel, falls by about 3.5% in the third quarter which corresponds to 2020Q3 in our analysis. Importantly, the quarantine is put in place in the second quarter, that is, in 2020Q2. However, because the lockdown is anticipated and creates large income risk, consumption (middle panel) and investment (right panel) fall in the very first period (2020Q1). This, in turn, brings forward in time the recession relative to when the bulk of the quarantine measures take place. Our baseline scenario is somewhat mild because it assumes unemployment rates to go up by 10 percentage points only. In an alternative scenario we assume an increase of 30 percentage points in unemployment rates, in which case the effects on macroeconomic aggregates triple as well.

The conditional transfer multiplier can be large

Figure 1 also illustrates how the transfers play out if they are implemented according to the CARES act, given the Q-shock. The blue lines show the results. Recall that the transfers amount to some $500 billion, roughly 10% of quarterly GDP in the US, and they are disbursed in 2020Q2. A key result is that the transfers matter not only for economic activity in that period, but also for the first period, before they are actually disbursed. Roughly speaking, the transfer payments reduce the drop of consumption, output, and investment in 2020Q1 to one third relative to the baseline scenario.

To understand this result, it is crucial to distinguish between unconditional transfers and transfers that are conditional on the recipient being unemployed. There is also an element of conditionality in the $1,200-payment per person under the CARES act, but this is relevant for a small fraction of the population only. Hence, we refer to it as ‘unconditional transfer’. Conditional transfers to the unemployed differ along two important dimensions. First, they are targeted to households who have high marginal propensities to consume. Second, and more importantly, the conditional transfer measure also limits the income risk ex ante, since the employed can expect additional funds in case they are to lose their jobs. The quarantine state becomes less frightful as a result.

Figure 2 Cumulative transfer multipliers

Note: Horizontal axis measures time in quarters. Transfers are being disbursed from period 2 onwards. Vertical axis measures the cumulative multiplier: the cumulative change in output up to a given horizon, divided by the cumulative transfer payments up to that horizon.

Figure 2 displays cumulative transfer multipliers for two alternative assumptions regarding monetary policy. In the left panel, we show results for the baseline where monetary policy responds to inflation in line with a conventional Taylor rule, in the right panel we show results under the assumption that monetary policy is very unresponsive to inflation. Monetary policy matters a great deal for the size of multiplier – a result familiar from earlier research on the fiscal multiplier. Focusing on period 2, we obtain a multiplier for the overall transfer package of the CARES act (black solid lines) of 0.4 in the baseline (left) and of 0.9 in case monetary policy is unresponsive (right).

But the figure also shows that these numbers mask large differences across conditional and unconditional transfers, shown by the blue and the red line, respectively. Importantly, it shows that the effectiveness of the transfer payments under the CARES act is mostly due to the conditional transfer component.  The multiplier for conditional transfers can be as large as two (unresponsive monetary policy), while the multiplier for unconditional transfers may be as small as 0.1 (baseline). The multiplier for the whole package is roughly the average of the two because conditional and unconditional transfers are of similar size.


In sum, we find that the transfer component as foreseen under the CARES act is likely to provide a welcome boost to the economy. Two aspects are particularly noteworthy. First, the transfers help to stabilize private sector spending and income in the early stage of the recession. Second, conditional transfers are particularly effective in this regard since they mitigate income risk due to the lockdown ex ante.

We also note two caveats. First, our simulation assumes that the transfers come online as foreseen under the CARES act. We abstract from problems of implementations which do seem to exist. Second, in our analysis we also abstract from scaring effects due to unemployment. These effects can be sizeable and, hence, maintaining employment rather than just income might be a priority for policy makers. We will take up these complications in future work.


Bayer, C, B Born, R Luetticke and G Müller (2020a), “The Coronavirus stimulus package: How large is the transfer multiplier?”, CEPR Discussion paper 14600.

Bayer, C, B Born and R Luetticke (2020b), “Shocks, Frictions, and Inequality in US Business Cycles”, CEPR Discussion Paper 14364.

Bénassy-Quéré, A, R Marimon, J Pisani-Ferry, L Reichlin, D Schoenmaker and B Weder di Mauro (2020) “COVID-19: Europe needs a catastrophe relief plan”,, 11 March 2020. 

Gali, J (2020), “Helicopter Money: The time is now”,, 17 March 2020.

7,139 Reads