Unit 5 Macroeconomic policy: Inflation and unemployment

5.7 The size of the multiplier and the impact of fiscal policy

In the multiplier model of Unit 3, we used simplified ways of modelling aggregate consumption, investment, trade, and government discretionary fiscal policy. This means there are a small number of variables from which the size of the multiplier is calculated, such as the marginal propensity to consume (MPC), the marginal propensity to import, and the tax rate. When we apply the model to the world, it is important to realise that in practice there is no single multiplier—a number—that applies at all times.

One modification follows directly from the discussion in Section 3.6, where we showed that households that are credit constrained will have an MPC close to one and households that are not will have an MPC close to zero: the MPC in the economy will depend on the share of each group in the economy. In a recession, after taking account of the effect of the automatic stabilizers, we would expect the share of credit-constrained households to rise, which implies that the average MPC in the economy would rise. A higher MPC increases the size of the multiplier and hence the effectiveness of discretionary fiscal stimulus in a recession.

With our assumptions so far, the multiplier in the model is always greater than one. We assume that output is determined solely by the level of aggregate demand and a change in aggregate demand directly changes output one-for-one and then indirectly by more in the subsequent rounds of expenditure, depending on the size of the multiplier.

However, the model can be extended in ways that mean the direct effect of a fiscal stimulus on output is less than one-for-one. This can result in an overall multiplier of less than one.

Crowding out

crowding out, crowded out

There are two quite distinct uses of the term. One is a negative effect that is observed when economic incentives displace people’s ethical or social motivations. In studies of individual behaviour, incentives may have a crowding out effect on social preferences. The second use of the term is to refer to the effect of an increase in government spending in reducing private spending, as would be expected for example in an economy working at full capacity utilization, or when a fiscal expansion is associated with a rise in the interest rate.

Suppose the economy is operating at full capacity utilization and there is very low unemployment. In such a situation, there may be little or no scope for output to rise. Then, a 1% increase in government spending on goods and services would displace or crowd out up to 1% of other spending in the economy. With complete crowding out, the multiplier would be zero. However, we would not normally expect a government to undertake a fiscal expansion when unemployment is very low—although it may do so in exceptional circumstances like war, as the US did in the later years of the Second World War and during the Vietnam War.

Another example of crowding out (and therefore, a lower multiplier) is if households think that higher government spending will be followed by higher taxes. In this case, some households may put aside more of their income to pay the extra taxes in the future. They save more now to keep their consumption path smoother. If this happened, the effect of the stimulus would be less.

The size of the multiplier will also depend on the expectations of firms and businesses. Households and firms not only react to policy changes, but also anticipate them. For example, if firms anticipate that the government will stabilize the economy following a negative shock, this will support business and consumer confidence, and the policymaker will be able to use a smaller stimulus. In this case, fiscal policy ‘crowds in’ private spending.

The multiplier and the financial crisis of 2007–2009

When the financial crisis in 2007–2009 led to the biggest fall in GDP in many economies since the Great Depression, the world’s policymakers expected an answer from economists: would fiscal policy help to stabilize the economy? The multiplier model, inspired by Keynes’ analysis of the Great Depression, suggested that it would. And despite scepticism among some economists, policymakers around the world embarked on fiscal stimulus programmes in 2008–2009. This prompt and decisive action was credited with helping to avert the persistent high unemployment of another Great Depression, as discussed in Unit 17 of The Economy 1.0.

The global financial crisis of 2008 revived interest in the multiplier. In 2012, a study published by economists Alan Auerbach and Yuriy Gorodnichenko showed how the multiplier varies in size according to whether the economy is in a recession or in an expansion.¹

For the US, their study suggested a $1 increase in government spending in the US raises output by about $1.50 to $2.00 in a recession, but only about $0.50 in an expansion. Auerbach and Gorodnichenko extended their research to other countries and found similar results. They also found that the effect of autonomous increases in spending in one country had spillover effects on the countries with which they trade. These effects were about the same magnitude as the indirect effects of second, third, and further rounds of spending in the home country.

How economists learn from facts The Mafia and the multiplier

reverse causality

If we are looking for evidence that one variable (x) causes another (y) and find that the variables are correlated, the explanation may be the reverse: that y causes x. For example, if we find that people who attend university earn more, does that mean that university increased their earning ability? Could it be that people with high earning potential are more likely to attend university? See also: correlation.

Economists need estimates of the multiplier to design their policy interventions. But finding out its size directly from data on government spending and changes in output will run into the problem of reverse causality: a fall in output may have led the government to increase spending. To get at the ‘pure’ effect of a change in spending on output, economists have used the Italian government’s struggle against the Mafia where spending cuts took place for reasons quite unrelated to the business cycle.

natural experiment

An empirical study that exploits a difference in the conditions affecting two populations (or two economies), that has occurred for external reasons: for example, differences in laws, policies, or weather. Comparing outcomes for the two populations gives us useful information about the effect of the conditions, provided that the difference in conditions was caused by a random event. But it would not help, for example, in the case of a difference in policy that occurred as a response to something else that might affect the outcome.

Antonio Acconcia, Giancarlo Corsetti, and Saverio Simonelli² adopted the natural experiment method to address the problem of reverse causality; they used data on Mafia-related dismissals of local politicians to isolate the variation in public spending that is not caused by variations in output.

After legal changes in 1991, the central government dismissed provincial councils in Italy that were revealed to have close links with the Mafia, and appointed new officials in their place. These technocrats cut local spending by 20% on average. The change in public spending was indirectly caused by Mafia infiltration, because that led to the replacement of government officials. However, because it was the change in government officials, rather than the involvement of Mafia, that led to spending cuts, the researchers can uncover the causal effect of a change in public spending on output. This situation is illustrated in Figure 5.9.

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https://www.core-econ.org/macroeconomics/05-macroeconomic-policy-07-multiplier-and-fiscal-policy.html#figure-5-9

Figure 5.9 Using Mafia infiltration to estimate the multiplier.

Using this method, the researchers were able to estimate multipliers of 1.5 at the local level.

Economists have used their ingenuity to come up with other methods of estimating the size of the multiplier and the implication of its operation for jobs in the context of the fiscal stimulus implemented in the US after the financial crisis (the American Recovery and Reinvestment Act of 2009, a $787 billion fiscal stimulus). The problem of reverse causality is very clear in this case. We are interested in how the stimulus affects output but measuring this is hard when output also affects the stimulus: US states that were more severely affected by the financial crisis would be expected to attract more stimulus money.

One approach to get around the problem of reverse causality is to make use of the fact that some of the spending in the US stimulus programme was distributed to US states using a formula that was unrelated to the severity of the recession experienced in each state. For example, some road repair expenditures funded by the stimulus package were based on the length of highway in each state.³

Given the formula for allocating road building funds and the fact that having more miles of highway has no direct effect on the change in unemployment, this allows us to answer the question: Were more jobs created in states that received more stimulus spending?⁴

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https://www.core-econ.org/macroeconomics/05-macroeconomic-policy-07-multiplier-and-fiscal-policy.html#figure-5-10

Figure 5.10 Using US stimulus highway spending to estimate the multiplier.

The results of studies using this approach estimated a multiplier of 2, and suggest that the American Recovery and Reinvestment Act created between one million and three million new jobs.