Macroeconomic Fluctuations, Inequality, and Human Development

Abstract

This paper examines the two-way relationship between inequality and economic fluctuations, and the implications for human development. For years, the dominant paradigm in macroeconomics, which assumed that income distribution did not matter, at least for macroeconomic behavior, ignored inequality—both its role in causing crises and the effect of fluctuations in general, and crises in particular, on inequality. But the most recent financial crisis has shown the errors in this thinking, and these views are finally beginning to be questioned. Economists who had looked at the average equity of a homeowner—ignoring the distribution—felt comfortable that the economy could easily withstand a large fall in housing prices. When such a fall occurred, however, it had disastrous effects, because a large fraction of homeowners owed more on their homes than the value of the home, leading to waves of foreclosure and economic stress. Policy-makers and economists alike have begun to take note: inequality can contribute to volatility and the creation of crises, and volatility can contribute to inequality. Here, we explore the variety of channels through which inequality affects fluctuations and fluctuations affect inequality, and explore how some of the changes in our economy may have contributed to increased inequality and volatility both directly and indirectly. After describing the two-way relationship, the paper discusses hysteresis—the fact that the consequences of an economic downturn can be long-lived. Then, it examines how policy can either mitigate or exacerbate the inequality consequences of economic downturns, and shows how well-intentioned policies can sometimes be counterproductive. Finally, it links these issues to human development, especially in developing countries.

Keywords:

• Inequality
• Development
• Financial crises
• Volatility
• Hysteresis

Acknowledgements

I wish to acknowledge helpful conversations with Miguel Morin, Deepak Nayyar, Anton Korinek, and José Antonio Ocampo.

Notes

For a critique of this paradigm, see, for instance, Stiglitz (2011a, 2011b) and the references cited there, including Stiglitz (2010c).

In particular, the UN Commission on Reforms of the Global Monetary and Financial System (United Nations 2009) emphasized the role of inequality as a major contributing factor to the current crisis. This work has spawned considerable research, including some cited elsewhere in this paper. For an excellent survey, see Jayadev (forthcoming) and the papers cited there. For a discussion of some empirical evidence, see Atkinson and Morelli (2010). Note that we are not claiming here that all financial crises are caused by inequality, or that inequality necessarily leads to a financial crisis. It is also important to note that the Gini coefficient may not adequately capture the appropriate notion of inequality for purposes of my discussion of economic fluctuations. If, for instance (as is in fact the case, see Dynan et al., 2004), there are marked differences in the marginal propensities to consume of the bottom 80% and the top 20%, then a better measure might be provided by the share of national income accruing to the top 20%. To the extent that fluctuations result from the ability of the financial elite to ‘capture’ the political process, to strip away regulations, then what matters is the share of income of that sector, or the share of income at the very top. See Acemoglu (2011).

There is a much older literature relating economic fluctuations to the functional distribution of income (which in turn is broadly related to inequality), growing out of the Kaldorian tradition. Akerlof and Stiglitz (1969) show, for instance, in a simple model that this can give rise to fluctuations of regular periodicity. For a more comprehensive discussion of the Kaldorian literature and subsequent related developments, see Jayadev (forthcoming).

Berg and Ostry (2011).

Breen and García-Peñalosa (2005) identified the cross-country linkage between inequality and volatility. They point out that their results are not driven by the high correlation of the two in Latin America.

There is even evidence that America's foreclosure crisis is having adverse effects on health. See Currie and Tekin (2011).

The absence of good insurance markets for these risks—which are among the most important that individuals face—is a major market failure. The explanation of this market failure is only partially accounted for by information asymmetries. See Stiglitz (1993).

These are some of the reasons that GDP is not a good measure of societal performance. See Fitoussi et al. (2010).

United Nations (2009).

This analysis focuses on the impact of the change in inequality, and focuses on the link through the accumulation of debt, which in turn is linked to credit crises. As we commented earlier, there are other links, such as that explored in Akerlof and Stiglitz (1969).

Although we do not pursue the question here, it may also be the case that the level of inequality is related to instability. For instance, at any given level of average income, more inequality may be associated with higher levels of consumption of durables, and purchases of durables are more volatile than purchases of food.

Thus, the build-up in debt is based partially on the basis of policy and partially on the basis of irrationality (as is the case implicitly in the work of Minsky). Deregulation, in particular, did not prevent the irrational build up of excessive risk. While it is true that the increased indebtedness enabled average Americans to avoid the decline in their standard of living that otherwise would have ensued, it is hard to reconcile the bubble itself with ‘rationality,’ and especially some of the extreme practices in the credit market.

For a recent paper attempting to construct an inequality induced credit cycle within a Dynamic Stochastic General Equilibrium (DSGE) framework, see Kumhof and Ranciere (2010).

For a more thorough discussion of these issues, see Jayadev (forthcoming).

See, for example, Atkinson and Stiglitz (1980), Besley (2004), and Besley and Persson (2009a, 2009b).

The US unemployment rate hit a peak of 10.2% in October 2009, while the peak reached by Germany was 7.9% in July 2009 and Sweden 9% in April 2010. In April, 2011, more than a year after the peak, the corresponding numbers were 9.0%, 6.2% and 7.5%. Data are from Eurostat and the US Bureau of Labor Statistics.

This is consistent with earlier empirical work based on cross-country regressions cited below showing that volatility is more associated with financial market problems than labor market rigidities.

See Fisher (1933). Greenwald and Stiglitz (1987, 1988a, 1988b, 1990b, 1993a) have revived and extended this theory, which has emphasized the adverse effects on balance sheets of unexpected price declines—or even price increases that are smaller than expected. In this crisis, considerable attention has been centered on these balance sheet effects. (For a review and extension to monetary policy, see Greenwald and Stiglitz, 1993b, 2003a).

There is a more general point: economic systems are not necessarily dynamically stable. The fall in wages that results from an increase in unemployment may move the economy away from the full employment equilibrium, rather than toward it. The implication is that it may be desirable for governments to intervene to prevent wage reductions; by contrast, policies of increasing wage flexibility may exacerbate this instability.

See Solow and Stiglitz (1968).

Theories of information asymmetries have explained why that is the case. See, for example, Greenwald and Stiglitz (1990a) for an analysis of the consequences and references.

Because there is an upper bound on employment, economies with greater volatility typically have a higher average unemployment rate (a higher gap between actual and potential output.)

While the notion that when unemployment is high, there is downward pressure on wages might seem obvious, in traditional neoclassical theory, lower employment (at a fixed level of capital) is associated with high real product wages. But such theories begin, in effect, by assuming full employment, and hence are of little relevance to the questions at hand. In efficiency wage theories (for example, Shapiro and Stiglitz 1984) it is easy to see how increased unemployment is associated with lower wages. So too in bargaining theories.

Of course, the Federal government could, through a revenue sharing program, offset the impact of the reduction in state and local tax revenues.

This is consistent with the empirical findings of Easterly et al. (2001a, 2001b).

This is a fundamental way in which most of modern macroeconomics has gone astray: in the standard models, the shocks to the economy are assumed to be exogenous.

For a broad discussion of these issues, see Ocampo and Stiglitz (2008) and the references cited therein.

Detragiache et al., (2006) and Gupta et al. (2011). See also Gormley (2007, 2010).

Rashid (2005).

Kumhof and Ranciere (2010).

The empirical significance of this effect remains controversial. See Mike Konczal (2011). One of the reasons that the subject is so controversial is that some are using the argument of ‘housing lock’ to suggest that there is a ‘new normal’ with a higher natural unemployment rate.

It is worth noting that some of the proposals being discussed for reducing the deficit in the United States could exacerbate both problems. For instance, removal of mortgage interest deductibility from the income tax (even in the future) will lower real-estate prices and have a particularly adverse effect on middle-income taxpayers. (There are alternative reform measures that might mitigate both problems.)

The other major category of cutbacks is investments, the effects of which typically are not felt for a long time.

To my knowledge, there is not an extensive literature confirming this conjecture, or identifying to what extent this being so depends on the nature of the political system. In democracies such as America where campaign contributions play a more important role, one might conjecture that the well-off are better able to resist cutbacks that would adversely affect them.

The final point differs from the first in that the final point focuses on the ‘wealth’ of the citizenry, and the first on the financial constraints facing government, recognizing: shifting money from the private sector to the public is costly, because of the distortions associated with taxation; and changes in the rules governing the split between the public and private sector are politically contentious.

This includes investments in R&D, with a consequent adverse effect on future growth. See, for example, Stiglitz (1994).

For example, see Dynarski and Sheffrin (1987) for a discussion of consumption and unemployment.

See Beck et al. (2005) among others.

See, for example, Besley (2004) and Besley and Persson (2009a, 2009b).

The models focused on second-order economic losses associated with relative prices being misaligned, ignoring the first-order losses resulting from prolonged gaps between the economy's actual and potential output.

Indeed, adjusting interest rates in response to inflation meant that when the inflation was ‘imported’ (e.g. when it arose from international prices, say of energy or food), it risked vastly distorting the economy—putting all the burden of adjustment on non-traded sectors, and imposing an even greater burden on the poor, as a result of the increased unemployment and lower wages that resulted.

In the United States, the Chairman of the Federal Reserve reportedly weighed in strongly against regulation of derivatives by the CFTC, supposedly an independent regulatory body. The heads of central banks often have influence that extends beyond the realm of their direct responsibility.

For a general theoretical discussion of these issues, see Stiglitz (2010a, 2010b).

Analyses of the effects from monetary authorities were not always consistent. As the end of QEII approached, they argued that there would be no market disruption, since the market had anticipated the end. But that raised the question, if they anticipated the end at the beginning, why should there have been much effect then? A partial answer was a claim that they believed in the ‘stock view,’ that prices (interest rates) depended on the stock of government bonds held by the public, which had been reduced by the intervention. Of course, in the meanwhile, during the period of QEII, the stock had been increased (and would increase even more after its end) as a result of the massive government debt. But, more broadly, the stock view is not totally coherent, or at least consistent with the rational expectations models on which some monetary authorities seem to rely. For in the presence of rational expectations, the Modigliani–Miller theorem for public finance says that public debt structure does not matter (Stiglitz, 1983, 1988). In practice, it almost surely does, but that is because markets are not well described by rational expectations and there are credit (liquidity) constraints that are not incorporated into the ‘stock’ view.

Stiglitz (2011).

See in particular unpublished work by Miguel Morin.

US Census income data, historical tables, Table H-9, [http://www.census.gov/hhes/www/income/data/historical/household/index.html], accessed 20 October 2011.

A Boston Fed research paper by DeRemer et al. (2004) finds that the period following the 2001 recession is even a ‘job-loss recovery’.

See, for example, Clark (1973), Fay and Medoff (1985) and Miller (1971).

Evidence that firms act in a way consistent with an increase in the effective interest rate includes cyclical movements in inventories and mark-ups. See, for example, Greenwald and Stiglitz (2003b).

The discussion of this section is based on the highly innovative work of Miguel Morin (2011).

To the extent that a country does not import machine goods (Germany), then the exchange rate effect is not of immediate concern. But even then, for firms that export, the exchange rate at the time of purchasing the capital good relative to that at the time they will be selling the good is also of concern.

The magnitude of these effects depends on the elasticity of substitution (along the ex ante production function), which can change over time and differ across sectors, as Morin (2011) has pointed out. As he also notes, this can have implications for differences in patterns of recovery across countries and over time.

The link between volatility and growth has been extensively discussed. There is a strong presumption that higher volatility raises the risk premium on investment and diminishes growth at least in the short to medium term. (In the standard Solow model, long-term growth is determined by the rate of population growth and the rate of technological progress. Volatility can affect long-term growth only by having an impact on those variables, which it may have.) See the discussion above and Ramey and Ramey (1995), Stiglitz et al. (2006), and Imbs (2007).

There is considerable evidence that firms act in a risk-averse way (Greenwald and Stiglitz, 1990a) and that, especially in downturns, investment is reduced as a result of financial constraints (Greenwald and Stiglitz, 1993a, 2003a; Greenwald et al., 1993).

The World Bank argues that ending malnutrition is crucial to human development, because of its irreversible effects on individuals' physical and intellectual development. See, for example, World Bank (2006) and the studies cited there.

US Department of Agriculture Economic Research Service figures, [http://www.ers.usda.gov/Briefing/FoodSecurity/stats_graphs.htm#food_secure].

See, for example, Atinc and Walton (1998) and Knowles et al. (1999).

Similarly, even in the urban sector in some countries there is a shift from the formal employment to informal employment, with adverse effects on security and possibly human development (less investment in human capital).

This effect arose in the current crisis even in developed countries: the bailout of the banks in the United States was centered on the largest institutions. The small and medium-sized banks (including community banks) remained with weak balance sheets years after the crisis, resulting in limited lending to SMEs. These SMEs depend, moreover, on collateral-backed loans, and the value of the principal source of collateral, real estate, was down markedly.

As Fitoussi et al. (2010) emphasize, GDP is not a good measure of well-being, and volatility and inequality themselves may lead to distortions in the measure. For instance, more unequal societies may have to spend a larger fraction of their resources on defending property rights—expenditures (like those for paying guards), which, while included in GDP, do not directly contribute to well-being (see Bowles and Jayadev, 2006). As the last crisis made so evident, bubbles are often associated with distorted prices, leading to exaggerated estimates of GDP before the crisis.

It is worth noting that since the marginal propensity to consume of low-income individuals (and especially the unemployed) is higher than that of upper-income individuals, policies that seek to maximize the bang for the buck are also policies that are egalitarian.