Who is affected by income inequality

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Your Practice. Popular Courses. Economy Economics. Table of Contents Expand. What Is Income Inequality? Understanding Income Inequality. Special Considerations. Key Takeaways Income inequality studies help to show the disparity of incomes among different population segments.

When analyzing income inequality, researchers commonly study distributions based on gender, ethnicity, geographic location, and occupation.

Case studies and analyses of income inequality, income disparity, and income distributions are provided regularly by a variety of top sources. The Gini Index is a popular way to compare income inequalities universally across the globe. An income gap refers to the difference in income earned between demographic segments.

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Compare Accounts. The offers that appear in this table are from partnerships from which Investopedia receives compensation. This compensation may impact how and where listings appear. Investopedia does not include all offers available in the marketplace. The Gini index, or Gini coefficient, is a measure of the distribution of income across a population. A decline in aggregate demand growth that is exogenous to interest rates will generally spur the Federal Reserve to reduce interest rates in order to stimulate consumption and investment and keep the economy at full employment.

Hence, the interest rate consistent with the economy reaching full employment the neutral rate will fall over time if this exogenous drag on demand growth continues or worsens. The evidence that this neutral rate has declined over time is compelling. Figure D shows the federal funds rate FFR as well as showing its average value over recent business cycles.

The evidence that the neutral FFR rate has been steadily falling since the s seems quite clear. Notes: Data are quarterly averages. Horizontal lines are averages over dates indicated. Shading indicates recessions. There is a relatively straightforward causal link between the rise of inequality and the chronic shortfall of aggregate demand: higher-income households have much higher savings rates than low- and middle-income households. So, as a dollar is transferred from the bottom and middle to the top of the income distribution, less of it is spent.

When the economy is functioning well, reduced consumer spending is offset by increased investment in plants and equipment, and demand is hence unaffected.

Here is how it could work. The reduced consumption stemming from this redistribution translates mechanically into higher savings. Higher savings in turn puts downward pressure on interest rates, and these lower interest rates induce more business investment in plants and equipment.

This interest rate adjustment hence ensures that the reduced consumption spending that follows the upward redistribution of income is matched by an increase in investment spending, and hence does not constitute a drag on growth in aggregate demand.

Keeping demand growth constant in the face of upward redistribution of income requires ever-lower interest rates, consistent with the data highlighted above. Interest rates cannot be moved below zero or at least not too much below zero for extended periods of time because negative interest rates will just induce households to hold their wealth in cash rather than interest-bearing or interest-subtracting!

Figure D showed that the U. The previous section noted that rising inequality will, all else equal, slow demand growth, as income is transferred to higher-savings households at the top of the income distribution.

The empirical question is just how much rising inequality has contributed to the decline in aggregate demand growth. Again, this decline in demand growth will show up in data as either a slowdown in overall growth, or a pronounced decline in the neutral interest rate.

Rachel and Smith , using a variety of techniques, estimate that the rise in inequality in recent decades will likely depress global interest rates by up to 0. They also note that while the global interest rate is important, country-specific rates can diverge from global rates due to country-specific factors.

Given that the U. Cynamon and Fazzari assemble a range of indicators estimating the potential of both rising inequality and rising household debt to act as a brake on demand growth. They highlight the role of rising household debt as a buffer that kept consumption for the bottom 95 percent of households from falling in the face of relatively slow income growth in the pre-Great Recession period.

This buffer was annihilated by the wealth lost when the housing bubble burst and ushered in the Great Recession in Cynamon and Fazzari argue that the decaying effect on demand of the transfer to the top, combined with the removal of the debt-consumption buffer, can largely explain the slow recovery from the Great Recession.

These findings are largely buttressed by Alichi, Kantenga, and Sole , who use a regression-based framework to estimate that changes in the American income distribution since had led to a demand-drag of more than 1 percent of total U. GDP by A key component of an analysis of demand drag caused by rising inequality is the savings rate of rich households. Figure E is constructed in the spirit of Cynamon and Fazzari , but makes some slightly different choices about income definitions and presentation of percentiles.

It shows average savings rates, from to , of the bottom four-fifths of the income distribution, as well as savings rates of households between the 80th and 90th percentiles, between the 90th and 95th percentiles, between the 95th and 99th percentiles, and of households in the top 1 percent. It replicates a procedure first identified by Maki and Palumbo to identify savings rates of the richest households.

The assumption used is that if a given income group held, say, half of all Treasury bonds in a given year, then this group was also responsible for half of the aggregate net acquisition of those bonds in a given year.

This gives us a measure of total savings by income group in each year. Unlike Cynamon and Fazzari , we include government transfers in our estimate of household income. Excluding these transfers from household income gives an estimate of how market-based income trends by themselves would have affected aggregate demand growth. Including the transfers provides an estimate of how much shifting inequality overall even including the generally equalizing effect of taxes and transfers actually slowed aggregate demand growth in recent decades.

The point of Figure E is simply that savings rates vary enormously across the income distribution. The economy-wide savings rate averaged This large difference in savings rates gives rising inequality a very long lever with which to influence trends in aggregate demand growth.

Table 2 shows the results of this procedure. Notes: Income shares do not sum to percent because the CBO income data includes households with negative incomes. The shares in the table above are effectively income shares of households with positive income. Negative income is never more than 2 percent of total income, so this failure to round to has only trivial effects on our calculations. The top panel of Table 2 shows the average savings rate for each of the income groups featured in Figure E.

Between and , the share of income claimed by the 95th to 99th percentile of households and the top 1 percent of households rose by 0. This figure is found in the bottom panel, which shows the demand drag potentially caused by rising inequality for the three periods.

While data restrictions keep us from getting average savings rates going back to as the SCF does not have reliable data before , there was a large redistribution between and as well. The implied demand drag of the — and — periods assumes that average savings rates across income percentiles from to characterize these periods as well.

By , the implied inequality-induced drag on aggregate demand that began in amounted to more than 4 percentage points of GDP every year. Even if we measure from , and we take as given the large but almost surely temporary decline in top 1 percent income shares from to , by inequality was imposing a drag of over 2 percentage points on aggregate demand growth. It is worth restating that this hit to the level of aggregate demand generated by rising inequality is cumulative : this demand drag is occurring each year by or This means that other macroeconomic influences must continuously ratchet up to keep demand growth from flatlining.

We of course know one of these macroeconomic demand resuscitators—the sharp fall in the neutral interest rate. Perhaps the best-known policy effort to boost aggregate demand growth in recent decades has been the American Recovery and Reinvestment Act ARRA of Passed to help stem the downward spiral of the Great Recession and financial crisis, ARRA provided the largest discretionary fiscal stimulus ever provided to the American economy.

Its year of peak effectiveness was , when, the Congressional Budget Office CBO estimated, it boosted aggregate demand growth and hence GDP growth by between 0.

This upper bound is roughly in line with the estimates above of the demand drag placed on the U. This means that to fully offset the demand drag stemming from inequality using available policy tools, policymakers would need to pass the equivalent of a new ARRA each year. Of course, in the years between and , other influences boosted demand as inequality sapped it. The most obvious influences were asset market bubbles in the stock and housing markets.

But absent transitory and damaging influences like large asset market bubbles, the scale of policy intervention needed to keep aggregate demand growth constant in the face of rising inequality is absolutely huge. The assertion that a large upward redistribution of income over the past generation has slowed growth in aggregate demand implies an increase in economy-wide savings because more of overall income is going to households that save more. That is why some skeptics could point to the most commonly referenced measure of economy-wide savings—the personal savings rate estimated each month by the Bureau of Economic Analysis BEA in the National Income and Product Accounts NIPA —to question our conclusion.

Over the past generation, this rate has fallen sharply: from 9. This rate spiked upward during and after the Great Recession, as households responded to huge wealth losses by cutting back on spending to rebuild their net worth.

This decline in the NIPA savings rate needs to be wrestled with. But both theory and evidence indicate that a falling NIPA personal savings rate can be reconciled with the story of inequality tamping down demand growth.

Of all the evidence, the strongest support comes from data that suggest that the NIPA personal savings rate is falling at least in part because it does not include a huge source of savings for the wealthy—unrealized capital gains. In regards to theory, interest rates are set by the interplay of desired savings and investment in the economy, not actual savings. In regards to data, while a cross-sectional redistribution of income from the bottom 95 percent to the top 5 percent will unambiguously reduce savings all else being equal holding everything else constant , in the real world it is not likely that everything else holds constant.

For example, as income was shifting to the top 1 percent from to , there were often periods when these households were reducing their own savings rates over time. As Cynamon and Fazzari document and the appendix of this paper shows, savings rates of top income households are quite volatile.

If rich households perceived the shift in income toward themselves over this period as permanent, a reduction in savings would have indeed been the textbook economic response. This time-series behavior of rich households with regard to their savings rates does not change the fact that a shift of income growth between income classes has potentially large effects on demand growth. Importantly, even when looking at the lowest savings rate recorded in a single year by top 1 percent households in the Survey of Consumer Finances data between and , the top 1 percent savings rate is still roughly 10 times higher than the savings rate of the bottom 80 percent.

Finally, and most importantly, it is likely that much of the rise in savings from our decades-long upward redistribution of income has actually materialized as unrealized capital gains, which are not captured by the NIPA personal savings rates. Essentially, there are two ways that households accrue net wealth: they consume less than the full amount of income they earn and save the remainder, or, their stock of accumulated past savings gains in value.

This gain in value of the stock of accumulated savings is a capital gain. Realized gains are captured in some income sources such as the CBO income data we used in Table 1.

The NIPA personal savings rate only measures savings out of current income flows—the difference between income and consumption spending in the U. Figure F shows the change in household net worth as a share of GDP. A broader definition of savings sometimes used by economists, this measure includes not only current income flows that are not consumed, but also the changes to wealth occurring from rising or falling asset prices, i.

This measure shows no obvious downward trend, although it clearly has become more volatile in recent years. As can be inferred from this data showing no downward trend in net worth, even in the face of falling flows of savings out of current income shown in NIPA data , capital gains have been large larger than flows of household savings and growing in recent decades. For example, as can be seen in Figure G , unrealized capital gains on financial assets constituted more than three quarters of the annual rise in household net worth on average between and The remaining quarter was contributed by household savings out of current income.

Further, the rise in capital gains is likely driven by a shift in corporate strategy that has redistributed more profits to shareholding households in the form of stock repurchases and less in dividend payments as shown in Figure H. Dividends and stock repurchases are just two different methods by which corporations can return the benefits of profits to their owners shareholders. If the firm instead decides to take money that was being used to repurchase stock and use it instead to just pay dividends to shareholders, these dividends would show up in the NIPA measure of personal income and would be captured in the personal savings rate.

Capital gains, again, are not measured as personal income and hence the change in corporate strategy to emphasize share repurchases over dividend payments affects measured savings rates. In short, much savings among high-income households in recent decades has likely shown up more on corporate balance sheets than on household balance sheets.

Further, the specific corporate actions—most notably the use of profits to repurchase stocks rather than pay dividends—has kept most measures of national savings from registering the pronounced increase in wealth deriving from the upward distribution of income. This helps explain why some measures of household savings show strong declines in recent decades even as total income claimed by high-income, high-savings households has increased dramatically: the extra savings resulting from that upward redistribution may be showing up in places besides household balance sheets.

Recent work has highlighted the possibility that rising inequality constitutes an exogenous shock to aggregate demand growth in the American economy. For years, this negative shock could largely be ameliorated by declining interest rates set by the Federal Reserve.

But since , the American economy has often found itself with a shortfall of aggregate demand even with short-term interest rates essentially at zero. This means that further increases in inequality will be damaging indeed to prospects of economic growth over the short and medium term unless some other lever of policy fills in the demand shortfall caused by the upward redistribution of income to high-saving households.

Policymakers need to get much more serious about avoiding this vicious spiral of chronic demand shortages caused in part by rising inequality degrading productive capacity. Getting serious would mean adopting a more expansionary monetary and fiscal policy portfolio public investments and expansions to social insurance programs than has been pursued in recent decades. But, as Taylor et al.

They also note that to move the dial on aggregate demand, policy efforts to spur wage increases will have to be much more ambitious than the adjustments to the federal minimum wage in recent decades. We need to enact a much larger raise in the minimum wage and advance policies to boost wage growth for workers making substantially more than the minimum wage. Policymakers should consider the links between inequality and informality because badly designed informality-reducing policies may increase inequality.

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