The transmission of monetary policy: The constraints on real estate loans are significant!

By Fergus Cumming (Bank of England) and Paul Hubert (Sciences Po – OFCE, France)

Does the transmission of monetary policy depend on the state of consumers’ debt? In this post, we show that changes in interest rates have a greater impact when a large share of households face financial constraints, i.e. when households are close to their borrowing limits. We also find that the overall impact of monetary policy depends in part on the dynamics of real estate prices and may not be symmetrical for increases and decreases in interest rates.

From the micro to the macro

In a recent article, we use home loan data from the United Kingdom to build a detailed measure of the proportion of households that are close to their borrowing limits based on the ratio of mortgage levels to incomes. This mortgage data allows us to obtain a clear picture of the various factors that motivated people’s decisions about real estate loans between 2005 and 2017. After eliminating effects due to regulation, bank behaviour, geography and other macroeconomic developments, we estimate the relative share of highly indebted households to build a measure that can be compared over time. To do this, we combine the information gathered for 11 million mortgages into a single time series, thus allowing us to explore the issue of the transmission of monetary policy.

We use the time variation in this debt variable to explore whether and how the effects of monetary policy depend on the share of people who are financially constrained. We focus on the response of consumption in particular. Intuitively, we know that a restrictive monetary policy leads to a decline in consumption in the short to medium term, which is why central banks raise interest rates when the economy is overheating. The point is to understand whether this result changes according to the share of households that are financially constrained.

Monetary policy contingent on credit constraints

We find that monetary policy is more effective when a large portion of households have taken on high levels of debt. In the graph below, we show how the consumption of non-durable goods, durable goods and total goods responds to raising the key interest rate by one percentage point. The grey bands (or blue, respectively) represent the response of consumption when there is a large (small) proportion of people close to their borrowing limits. The differences between the blue and grey bands suggest that monetary policy has greater strength when the share of heavily indebted households is high.

It is likely that there are at least two mechanisms behind this differentiated effect: first, in an economy where the rates are partly variable[1], when the amount borrowed by households increases relative to their income, the mechanical effect of monetary policy on disposable income is amplified. People with large loans are penalized by the increase in their monthly loan payments in the event of a rate hike, which reduces their purchasing power and thus their consumption! As a result, the greater the share of heavily indebted agents, the greater the aggregate impact on consumption. Second, households close to their borrowing limits are likely to spend a greater proportion of their income (they have a higher marginal propensity to consume). Put another way, the greater the portion of your income you have to spend on paying down your debt, the more your consumption depends on your income. The change in income related to monetary policy will then have a greater impact on your consumption. Interestingly, we find that our results are due more to the distribution of highly indebted households than to an overall increase in borrowing.

Our results also indicate some asymmetry in the transmission of monetary policy. When the share of constrained households is large, interest rate increases have a greater impact (in absolute terms) than interest rate cuts. This is not completely surprising. When your income comes very close to your spending, running out of money is very different from receiving a small additional windfall.

Our results also suggest that changes in real estate prices have significant effects. When house prices rise, homeowners feel richer and are able to refinance their loans more easily in order to free up funds for other spending. This may offset some of the amortization effects of an interest rate rise. On the other hand, when house prices fall, an interest rate hike exacerbates the contractionary impact on the economy, rendering monetary policy very powerful.

Implications for economic policy

We show that the state of consumers’ debt may account for some of the change in the effectiveness of monetary policy during the economic cycle. However, it should be kept in mind that macro-prudential policy makers can influence the distribution of debt in the economy. Our results thus suggest that there is a strong interaction between monetary policy and macro-prudential policy.

[1] Which is the case in the United Kingdom.

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Are our inequality indicators biased?

By Guillaume Allègre

The issue of inequality is once again at the heart of economists’ concerns. Trends in inequality and its causes and consequences are being amply discussed and debated. Strangely, there seems to be a relative consensus about how to measure it [1]. Economists working on inequality use in turn the Gini index of disposable income, the share of income held by the richest 10%, the inter-decile ratio, and so on. All these measures are relative in character: If the income of the population as a whole is multiplied by 10, the indicator doesn’t change. What counts is the income ratio between the better off and the less well off. But could inequality and the way it changes be measured differently?

France’s inequality monitoring body is currently discussing not only trends in the income ratio between the more and less well-off, but also changes in the income gap: “In one year, the richest 10% receive on average about 57,000 euros, and the poorest 10% 8,400 euros: a difference of 48,800 euros, equivalent to just over 3.5 years of work paid at the minimum wage (Smic). This gap rose from 38,000 euros in 1996 to 53,000 euros in 2011, then fell to 48,800 euros in 2017.” Measuring changes in the income gap does not seem relevant. Let’s take two people with incomes of 500 and 1,000 euros, then multiply their incomes by 10: the income ratio is stable, but the income gap is multiplied by 10. Has inequality increased, is it stable or has it decreased? Using the income gap as a measure, it has increased, but it is stable according to the ratio. We believe it may have actually decreased.

Indeed, in France today, the differences in living conditions, lifestyles and well-being are perhaps greater between someone with an income of 500 euros, which leaves them in dire poverty, and someone with an income of 1,000 euros, which puts them at the poverty line, than between a person with an income of 5,000 euros, who can be described as well-off, and a person earning 10,000 euros, who can be described as very well-off. These last two people share similar lifestyles, even if the latter probably lives in a slightly larger and better-situated home, and frequents more luxurious restaurants. In other words, subtracting 10% of income from a very wealthy person probably has less impact than subtracting 10% from someone at the poverty line. There is abundant literature on risk aversion showing that people are willing to pay more than 10% of their income when it is high to protect against a 10% drop in income when it is low. This is, moreover, one of the justifications for a progressive tax: a greater percentage is taken from the better off, but the sacrifice is supposed to be equal because, according to marginalist theory, contributive capacity grows faster than income (or utility increases less than proportionately compared to income).

If this argument is accepted, we could conclude that at a constant level of relative inequality (Gini index, income ratio between the richest and poorest), all other things being equal, a richer society would in practice be more egalitarian, in the sense that its citizens share a more comparable way of life or well-being. Intuition tells us that this is true for large gaps in wealth (such as the 10-fold increase in earnings in the example above). If this is true, then comparisons of relative inequality made over very long periods of time or between developed and developing countries need to be kept in perspective. When Thomas Piketty shows that the richest 10% captured 50% of income between 1780 and 1910, we could then conclude that inequality has decreased over that period!

Milanovic and Milanovic, Lindert and Williamson have developed concepts that take into account this wealth effect over a very long-term historical perspective: the “inequality frontier” is the maximum inequality possible in a society taking into account the fact that the society must guarantee the livelihoods of its poorest members (the minimum income to live): in an economy with very little surplus (where the average discretionary income is low), the maximum possible inequality will be low [2]; in a very well-off economy, the maximum possible Gini coefficient will be close to 100 percent [3]. The “extraction ratio” is the current Gini divided by the maximum possible Gini. The wealthier a country is, the lower the maximum possible Gini coefficient, and the more – at equal Ginis – the extraction ratio will be low. One could also calculate a “discretionary income Gini” (in the sense of disposable income minus the minimum subsistence income) [4].

It can be argued that when comparing inequality in two societies at different levels of development, the extraction ratio is a better indicator of inequality than the available income Gini [5] or other indicators of relative inequality. One conclusion reached by Milanovic et al.: “Thus, although inequality in historic preindustrial societies is equivalent to that of industrial societies today, ancient inequality was much larger when expressed in terms of maximum feasible inequality. Compared to the maximum feasible inequality, current inequality is much lower than that in ancient societies”. According to the authors, in the early 2000s, the maximum possible Gini was 55.7 in Nigeria and 98.2 in the US: the comparison of inequality between the two countries will then be very different depending on whether the indicator chosen is the income Gini or the extraction ratio. On the other hand, there will be little difference between the United States and Sweden (maximum achievable Gini of 97.3) despite an average income difference of 45%. The effect is in fact saturated since the Swedish income is already 40 times the subsistence minimum (400 dollars per year in purchasing power parity) and the American, 58 times. In the authors’ approach, the subsistence minimum is set in purchasing power parity and is fixed between countries and over time. But is the subsistence minimum really 400 dollars a year in Sweden today? When comparing inequality in the United States and Sweden today, is this subsistence minimum relevant? Taking a significantly higher minimum level of subsistence could change the comparison of inequality, even in developed countries (for a comparable living standards Gini, is Switzerland really more egalitarian than France?). The problem then is to establish a minimum subsistence income amount [6].

The choice of an inequality indicator depends on the objective pursued. If the idea is to compare inequalities in living conditions across time or between countries, the discretionary income Gini might be relevant. On the other hand, if there is concern that excessively high incomes present a danger for democracy (a position developed in particular by Stiglitz in The Price of Inequality), the measure of relative inequality as calculated by the share of income captured by the wealthiest 1% seems more relevant.

When comparing countries that are closely related in terms of development, there are other, perhaps more important, limitations to comparing living standard Ginis. Given the same income inequality, a country where public spending on health, housing, education, culture, etc. is higher will (probably) be more egalitarian (unless public spending goes disproportionally to the better off). The issue of housing is also important, as it weighs heavily in household budgets: all other things being equal, high rents due to a constrained housing supply will increase inequality (tenants are poorer on average today). But it is difficult to take into account this effect in comparisons or trends, because the price of housing may reflect an improvement in quality or better amenities. In addition, inequality between landlords and tenants is not taken into account in the usual calculation of the standard of living: with equal income, an owner who has finished repaying the mortgage is better off than a tenant, but the fictitious rent that the owner receives does not enter the calculation of their standard of living. Finally, and without being exhaustive, the issue of hours of work and household production also complicates the equation: a difference in income can be linked to a difference in working hours, especially if one of the spouses in a couple (most often the woman) is inactive or works part-time. However, the inactive spouse can engage in household production (including childcare) that is not taken into account in statistics: the difference in standard of living with the bi-active couple is less than what is implied by the difference in incomes. Statistics do not usually take this effect into account because it is difficult to assign a value to household production.

It can be seen that the measurement of income and the standard of living, and therefore inequality, is imperfect. The wealth effect (at an equal standard of living Gini, a richer society is probably more egalitarian, all things being equal) is a limit, among others, some of which are probably more important when comparing developed economies. On the other hand, this wealth effect could be relatively significant if one wants to compare inequalities in living conditions between the France of 1780 and that of 1910 and a fortiori of today.

[1] Whereas it was prominent from the early 1970s to the end of the 1990s: see in particular the work of Atkinson, Bourguignon, Fleurbaey and Sen.

[2] Milanovic et al. give the following example: consider a society of 100 individuals, 99 of whom are in the lower class. The subsistence minimum in this society is 10 units and the total income 1,050 units. The sole member of the upper class receives 60 units. The Gini coefficient associated with this distribution (the maximum possible Gini) is only 4.7 percent.

[3] In fact, the maximum possible Gini rises quickly: if in the previous country, the income increases to 2,000 units and the dictator extracts all the surplus (1,010 units), the Gini leaps to 49.5.

[4] The disposable income Gini, or the extraction ratio, shares some of the characteristics of the Atkinson index, including the idea of differentiating among the wealthiest and the poorest. Nevertheless, the Atkinson index remains a relative indicator of inequality: if all incomes are multiplied by 10, the indicator remains constant. The index satisfies average independence, which is generally sought among inequality indicators, but which we seek to go beyond here.

[5] The two indicators do not measure the same concepts. First, it may be interesting to use several indicators, but multiplying the number of indicators raises the problem of readability, so one must choose. The choice of an indicator is based on a normative judgment since, at least implicitly, the idea is to reduce inequality according to the measure chosen (there is a consensus among economists that, all else being equal, less inequality is preferable).

[6] Especially since this income must be consistent over time or between countries if the objective is to capture a trend or make a comparison.

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Negative interest rates: Challenge or opportunity for Europe’s banks?

By Whelsy Boungou

It has been five years since commercial banks, in particular those in the euro zone, have faced a new challenge, that of continuing to generate profit in an environment marked by negative interest rates.

At the onset of the 2007-2008 global financial crisis, several central banks implemented new “unconventional” monetary policies. These consisted mainly of massive asset purchase programmes (commonly known as Quantitative Easing, QE) and forward guidance on interest rates. They aimed to lift the economies out of crisis by promoting better economic growth while avoiding a low level of inflation (or even deflation). Since 2012, six central banks in Europe (Bulgaria, Denmark, Hungary, Sweden, Switzerland and the European Central Bank) and the Bank of Japan have gradually introduced negative interest rates on bank deposits and reserves, in addition to the unconventional measures already in force. For example, the ECB’s deposit facility rate now stands at -0.40% (see Figure 1). Indeed, as indicated by Benoît Cœuré [1], the implementation of negative rates aim to tax banks’ excess reserves to encourage them to use these to boost the credit supply.

However, the implementation of negative rates has raised at least two concerns about the potential effects on bank profitability and risk-taking. First, the introduction of negative rates could hinder the transmission of monetary policy if this reduces banks’ interest margins and thus bank profitability. In addition, the lowering of credit rates for new loans and the revaluation of outstanding loans (mainly at variable rates) reduces banks’ net interest margin when the deposit rate cannot fall below the Zero Lower Bound. Second, in response to the impact on margins, the banks could either reduce the share of nonperforming loans on their balance sheets or look for other assets that are more profitable than loans (“Search-for-yield”). In a recent article [2], we used panel data from 2442 banks from the 28 member countries of the European Union over the period 2011-2017 to analyse the effects of negative rates on bank behaviour with respect to profitability and risk-taking. Specifically, we asked ourselves three questions: (1) What is the impact of negative rates on banks’ profitability? (2) Would negative rates encourage banks to take more risks? (3) Would the pressure on net interest margins from negative rates encourage banks to take more risk?

At the conclusion of our analysis, we highlight the presence of a threshold effect when interest rates fall below the zero bar. As can be seen in Figure 2, a 1% reduction in the central bank deposit rate reduced banks’ net interest margins by 0.429% when rates are positive, and by 1.023% when they are negative. Thus, negative rates have a greater impact on banks’ net interest margins than do positive rates. This result points to the presence of a threshold effect at zero. In addition, in response to this negative effect on margins (and in order to offset losses), the banks responded by expanding their non-interest rate activities (account management fees, commissions, etc.). As a result, in the short and medium term there was no indication that the banks resorted to riskier positions. However, the issue of risk-taking may eventually arise if negative rates persist for a long time and the banks continue to suffer losses on net interest margins.

[1] Coeuré  B.  (2016). Assessing the implication of negative interest rates.  Speech at the Yale Financial Crisis Forum in New Haven. July 28, 2016.

[2] Boungou W. (2019). Negative Interest Rates, Bank Profitability and Risk-taking. Sciences Po OFCE Working Paper no. 10/2019.

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The impact on redistribution of the ECB’s monetary policy

By Jérôme Creel and Mehdi El Herradi

A few weeks before Christine Lagarde assumes the presidency of the European Central Bank (ECB), it may be useful to examine the balance sheet of her predecessors, not only on macroeconomic and financial matters but also with respect to inequality. In recent years, the problem of the redistributive effects of monetary policy has become an important issue, both academically and at the level of economic policy discussions.

Interest in this subject has grown in a context marked by the conjunction of two factors. First there has been a persistent level of inequality in wealth and income, which has been hard to reduce. Then there are the activities of the central banks in the advanced economies following the 2008 crisis to support growth, particularly through the implementation of so-called “unconventional” measures [1]. These measures, mainly manifested in quantitative easing (QE) programmes, are suspected to have increased the prices of financial assets and, as a result, favoured wealthier households. At the same time, the low interest rate policy could have resulted in a reduction in interest income on assets with fixed yields, most of which are held by low-income households. On the other hand, the real effects of monetary policy, particularly on changes in the unemployment rate, could help keep low-income households in employment. The ensuing debate, which initially broke out in the United States, also erupted at the level of the euro zone after the ECB launched its QE programme.

In a recent study focusing on 10 euro zone countries between 2000 and 2015, we analysed the impact of the ECB’s monetary policy measures – both conventional and unconventional – on income inequality. To do this, we drew on three key indicators: the Gini coefficient, both before and after redistribution, and an interdecile ratio (the ratio between the richest 20% and the poorest 20%).

Three main results emerge from our study. On the one hand, a restrictive monetary policy has a modest impact on income inequality, regardless of the indicator of inequality used. On the other hand, this effect is mainly due to the southern European countries, especially in the period of conventional monetary policy. Finally, we found that the redistributive effects of conventional and unconventional monetary policies do not differ significantly.

These results thus suggest that the monetary policies pursued by the ECB since the crisis have probably had an insignificant and possibly even favourable impact on income inequality. The forthcoming normalization of the euro zone’s monetary policy could, on the contrary, increase inequality. Although this increase may be limited, it is important that decision-makers anticipate it.

[1] For an analysis of the expected impact of the ECB’s unconventional policies, see Blot et al. (2015).

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The OFCE optimistic about growth – “As usual”?

By Magali Dauvin and Hervé Péléraux

In the spring of 2019, the OFCE forecast real GDP growth of 1.5% for 2019 and 1.4% for 2020 (i.e. cumulative growth of 2.9%). At the same time, the average forecast for the two years compiled by Consensus Forecasts[1] was 1.3% each year (i.e. 2.6% cumulative), with a standard deviation around the average of 0.2 points. This difference has led some observers to describe the OFCE forecasts as “optimistic as usual”, with the forecasts of the Consensus or institutes with less favourable projections being considered more “realistic” in the current economic cycle. Continue reading “The OFCE optimistic about growth – “As usual”?”

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Business investment hurt by Brexit

By Magali Dauvin

At a time when the outlook for world trade outlook remains glum [1], British domestic demand is struggling to remain dynamic: household consumption has run out of steam at the end of the year, while investment fell by 1.4 points in 2018.
This latest fall can be attributed almost entirely to the investment of non-financial corporations [2] (55% of GFCF in volume), which fell consecutively during the four quarters of the year (Figure 1), for a total fall of -3.7% in 2018. Continue reading “Business investment hurt by Brexit”

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Climate justice and the social-ecological transition

By Éloi Laurent

There is something deeply reassuring about seeing the growing scale of climate markets in numerous countries around the globe. A section of the youth are becoming aware of the injustice they will suffer as a result of choices over which they do not (yet) have a say. But the recognition of this inter-generational inequality is running up against the wall of intra-generational inequality: it will not be possible to implement a real ecological transition without dealing with the social question here and now, and in particular the imperative to reduce inequality. In other words, the ecological transition will be social-ecological – or it will not be. This is the case in France, where the national ecological strategy, currently 90% ineffective, needs to be thoroughly overhauled, as proposed in the new OFCE Policy Brief (no. 52, 21 February 2019). Continue reading “Climate justice and the social-ecological transition”

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On French corporate immaterial investment

By Sarah Guillou

A note on the immaterial singularity of business investment in France from 26 October 2018 highlighted the significant scale of investment in intangible assets by companies in France. In comparison with its partners, who are similar in terms of productive specialization, the French economy invests relatively more in Research and Development, software, databases and other types of intellectual property. Continue reading “On French corporate immaterial investment”

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German women work less than French women

By Hélène Périvier and Gregory Verdugo

In terms of the employment rate, French women work less than German women: in 2017 the employment rate of women aged 15 to 64 was 67.2% in France against 75.2% in Germany. But this commonly used indicator does not take into account that to arrange their time German women are more likely to be in part-time work than French women. Continue reading “German women work less than French women”

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Why some countries have fared better than other after the Great Recession

by Aizhan Shorman and Thomas Pastore

The European labor market is characterized by a great economical and institutional divergence. On the one hand, there is the German miracle constituted in part by a decrease in unemployment rate during the Great Recession. On the other, there is high unemployment in southern European countries. Continue reading “Why some countries have fared better than other after the Great Recession”

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