key: cord-1005400-ote6razl
authors: Drescher, Katharina; Fessler, Pirmin; Lindner, Peter
title: Helicopter money in Europe: New evidence on the marginal propensity to consume across European households
date: 2020-07-25
journal: Econ Lett
DOI: 10.1016/j.econlet.2020.109416
sha: b1d77f4061171af4a6525ac3630f1584dd964627
doc_id: 1005400
cord_uid: ote6razl

The recent spread of COVID-19 has led to the worst economic crisis since the 1930s. To boost demand after the crisis, direct monetary transfers to households are being discussed. Using novel microdata from the Eurosystem Household Finance and Consumption Survey (HFCS), we study how much of such a transfer households would actually spend. We do so by exploiting the unique opportunity that the new wave of the survey included an experimental question to calculate the marginal propensity to consume from hypothetical windfall gains. Our results show that households on average spend between about 33% (the Netherlands) and 57% (Lithuania) of such a transfer. In all countries, answers are clustered at spending nothing, spending 50% and spending everything. Marginal propensities to consume decrease with income but are not as clearly related to wealth.

In recent months helicopter money has been widely discussed as a potential tool to boost the economy once the COVID-19 health crisis is under control. Several blog posts and new working papers discuss the issue. 1 Nevertheless, cross country empirical evidence is still scarce on how helicopter money is actually spent.

The literature on the marginal propensity to consume (MPC) is, theoretical as well as empirical, among the largest and oldest fields in economics. Japelli and Pistaferri (2010) provide an excellent overview. In a more recent contribution, Japelli and Pistaferri (2014) base their analysis on a hypothetical question in an Italian household survey to examine the However, the MPC resulting from windfall gains has to the best of our knowledge not been examined on the basis of internationally comparable microdata for a large set of countries including the whole balance sheet of households. Note, that using a question on hypothetical windfall gains instead of actual gains allows to include all households (represented by the sample) in the analysis, while analyses of actual gains are often restricted to small subsets of the population. We contribute to the literature by examining the MPC out of a windfall gain for a set of 17 European countries (all euro area countries excluding Spain and Estonia) based on a harmonized survey question within the main European survey to analyze household finances. We estimate the average MPC across countries and the full distribution of income and wealth. We find heterogeneity across country means as well as strong differences in distributional patterns with regard to extreme saving or spending 1 See for example: https://voxeu.org/article/fight-covid-pandemic-policymakers-must-move-fast-and-break-behavior. While the average MPC clearly decreases with income, it shows no correlation with wealth. We conclude that a standardized monetary intervention via helicopter money in the euro area would lead to very heterogenous effects across different countries, but also within countries across households.

The data come from the third wave of the Eurosystem HFCS and was published in Imagine you unexpectedly receive money from a lottery, equal to the amount of income your household receives in a month. What percent would you spend over the next 12 months on goods and services, as opposed to any amount you would save for later or use to repay loans?

Following the existing literature, we estimate the marginal propensity to consume out of such a windfall gain. In particular, we are interested in its distribution across household 2 Detailed information about the survey can be found at https://www.ecb.europa.eu/pub/economicresearch/research-networks/html/researcher_hfcn.en.html. 3 All HFCS data is multiply imputed five times. However, not all countries included the experimental question into their list of variables to be imputed. That is why for calculations of the MPC we can only use 58,515 observations out of the total 60,114 for all countries (see table 1). We use Rubin's Rule for all calculations.

Journal Pre-proof incomes as well as across countries, because both are crucial to designing a potential helicopter money policy and evaluating its potential impact. On top of that, our survey allows for an assessment of the MPC across the distribution of net wealth as well. Table 1 shows descriptions of all variables we use in the analysis. Summary statistics of the surveys and main variables used in our empirical analysis are presented in table 2.

[ Table 1 here]

[ Table 2 here]

We use straightforward tools to describe the empirical results of the question at hand.

Note, however, that we use both complex survey population weights and multiple imputations for all statistics shown. While the multiple imputations would not be very important for the experimental question alone, they are crucial for obtaining the correct correlations with income and wealth. We show the full distribution of answers to the experimental question using a detailed histogram. We calculate the average marginal propensity to consume across all countries. And we use two tools to describe large datasets while keeping the micro perspective alive:

First, we use locally weighted non-parametric linear regressions (loess) to estimate the share of households providing an answer at the end of the spectrum by saying that they spend nothing (MPC=0) or all (MPC=1) across the full distribution of gross income 4 (using the cumulative distribution function).

Second, we use binned scatter plots where average MPCs of bins including an equal number of households (weighted observations) are calculated across gross income and net wealth. In a second step we also use binned scatter plots of the same variables, but residualized. Thus, by using linear regression and the Frisch-Waugh-Lovell theorem variation explainable by a set of control variables is filtered out before plotting. 4 We use the cdf of gross income for several reasons: First, net income is not available in the HFCS. Second, because of potential measurement error we only use the ranking of households and not their actual income values. The ranking should also be highly correlated with the ranking according to net income. Figure 1 shows the full range of answers to the question on how much of the windfall gain would be spent. One can clearly see that the answers are clustered at three points: saving all (MPC=0), saving/spending half (MPC=0.5) and spending all (MPC=1). This finding holds also at the country level for all countries, however in varying degrees. It also ties in with the findings of the literature discussed. In some countries the share of those who save everything is higher across the full distribution of gross income. In others the share of those who spend everything dominates. In some countries the correlation with income is much stronger than in others. All these patterns illustrate that overall the effects of euro area-wide helicopter money might be rather heterogenous not only on average across countries but also in terms of different patterns across and within countries. The residualized plots control for country dummies 5 , households size, age of the reference person based on 15 categories and a dummy variable indicating that at least one person living 5 Country-level fixed effects should control for differences in the levels of income or wealth due to institutional differences or differences in national price levels.

Journal Pre-proof in the household is 65 years or older, and wealth (in the case of income) or income (in the case of wealth). The data offer the unique opportunity to analyze average MPC together with wealth. One can clearly see that there is hardly any correlation between households´ net wealth and their MPC. By contrast, there is clearly a negative correlation between MPC and income. One reason for this difference might be that income is immediately available for spending. Conversely, a large part of household wealth such as housing, cars or other real assets but also part of the financial assets is not directly available for spending but would need to be liquidated or used as a collateral first.

[ Figure 4 here]

Using microdata comparable across 17 euro area countries, we find that the average marginal propensities to consume (MPCs) vary considerably across countries. The MPC is lowest − at about 33% − in the Netherlands and Portugal and highest − at about 57% − in Greece and Lithuania. Patterns behind average MPCs differ strongly across countries. MPCs are negatively correlated with gross income but the relationship to wealth is less clear.

Based on the empirical evidence at hand we conclude that helicopter moneyif applied equally across euro area countrieswould likely have very heterogenous effects across different countries. But also within countries, the effects would be related to the spending patterns along the income distribution, with a relatively stronger impact on goods and services consumed by lower income households exceeding their proportion of general spending/income.

Given the higher MPC in lower income groups, one policy conclusion could be that a lump sum transfer is preferable to an inequality-preserving amount proportional to net income. 16-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, 80-84, 85 and older dhaged65plus old age Household members aged 65 or more J o u r n a l P r e -p r o o f Journal Pre-proof 

Would helicopter money be spent? New Evidence for the Netherlands