Month: March 2017

Is “Moral Outrage” Largely Self-Serving?

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Image result for angry protester

That seems to be the case, according to a new study. Reason reports,

When people publicly rage about perceived injustices that don’t affect them personally, we tend to assume this expression is rooted in altruism—a “disinterested and selfless concern for the well-being of others.” But new research suggests that professing such third-party concern—what social scientists refer to as “moral outrage”—is often a function of self-interest, wielded to assuage feelings of personal culpability for societal harms or reinforce (to the self and others) one’s own status as a Very Good Person.

…To test this guilt-to-outrage-to-moral-reaffirmation premise, Rothschild and Keefer conducted five separate studies assessing the relationships between anger, empathy, identity, individual and collective guilt, self perception, and the expression of moral outrage.

Their findings?:

  1. Triggering feelings of personal culpability for a problem increases moral outrage at a third-party target.
  2. The more guilt over one’s own potential complicity, the more desire “to punish a third-party through increased moral outrage at that target.”
  3. Having the opportunity to express outrage at a third-party decreased guilt in people threatened through “ingroup immorality.”
  4. “The opportunity to express moral outrage at corporate harm-doers” inflated participants perception of personal morality.
  5. Guilt-induced moral outrage was lessened when people could assert their goodness through alternative means, “even in an unrelated context.”

The article concludes,

These findings held true even accounting for things such as respondents political ideology, general affect, and background feelings about the issues.

Ultimately, the results of Rothschild and Keefer’s five studies were “consistent with recent research showing that outgroup-directed moral outrage can be elicited in response to perceived threats to the ingroup’s moral status,” write the authors. The findings also suggest that “outrage driven by moral identity concerns serves to compensate for the threat of personal or collective immorality” and the cognitive dissonance that it might elicit, and expose a “link between guilt and self-serving expressions of outrage that reflect a kind of ‘moral hypocrisy,’ or at least a non-moral form of anger with a moral facade.”

I’m reminded of something economist Deirdre McCloskey wrote: “You sit down with a cup of dark coffee and a nice croissant to read the New York Times, venting daily your hatred of the cruelties recorded there, and as a result are yourself saved, regardless of whether policies of “protection” advocated in its pages do the poor and tortured any actual good.”

Do Social Networks Matter More Than Institutions?

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Image result for world connection cell phone

I’ve posted before about McKinsey’s findings regarding digital globalization. They reported,

Data flows directly accounted for $2.2 trillion, or nearly one-third, of [globalization’s] effect [in a decade]—more than foreign direct investment. In their indirect role enabling other types of cross-border exchanges, they added $2.8 trillion to the world economy. These combined effects of data flows on GDP exceeded the impact of global trade in goods.

This in turn supported research by economist Andreas Bergh, who found that

the poverty-decreasing effect of globalization is bigger in countries where institutions are worse. The graph below shows how the marginal effect of information flows on poverty varies depending on the level of bureaucratic quality. The slope looks the same for all institutional indicators, suggesting that globalization is especially important for the poor in countries with high corruption levels and inefficient public sectors.

A new Harvard working paper supports these findings, suggesting that communication networks and social interactions are more important than institutions. The authors explain,

Telling institutional versus socio-technological interpretations apart has been challenging. This paper tests these two hypotheses by measuring convergence in income across Colombian municipalities along two distinct geospatial divisions: one institutional, one socio-technological. The institutional explanation would emphasize the role that belonging to a particular departamento, or state, has on the institutional arrangements and the provision of public goods, thus affecting the incentive structure of agents to operate with better technology.

Although Colombia is a unitary republic, not a federation, states have significant autonomy1 . Studies on Colombia, including those that take an institutional perspective such as Acemoglu et al (2015)…utilize state-level data, as do almost all studies of intra-national unconditional convergence worldwide. Under the institutional assumption, a municipality should tend to converge to the income of the state to which it belongs.

The socio-technological explanation would predict that municipal income convergence should occur within the cluster of municipalities that interact intensely with each other, whether or not they belong to the same state. This is due to the need for intensive social interactions for knowhow to diffuse. To form these socio-technological groupings, we utilize a unique dataset of cellphone calls to group municipalities so that most of the phone calls happen within rather than between these clusters. To facilitate comparison with the 32 states of the institutional state aggregation, we group municipalities into 32 communication clusters…Thus, communication clusters are groups of municipalities that are densely connected through phone calls, meaning that they are significantly more likely to call members of the cluster than they are to call other municipalities (pgs. 4-5).

The authors conclude,

To test these two interpretations in a more direct way, we use municipal level data for Colombia, which we aggregate using two different grouping criteria: the departamento or state to capture institutional variation; and the communication cluster to which a municipality belongs, to capture the intensity of social interaction. We use formal wages per capita as our measure of income per capita, as it can be measured at the municipal level. We use cellphone data to group municipalities into communication clusters of intense interaction.

In this setting, we find evidence of absolute convergence in Colombia at the municipal level. We find evidence that the process is accelerated when the municipality belongs to a richer communication cluster. However, we do not find evidence of a positive influence of belonging to a richer state. We interpret these results as evidence in favor of the idea that obstacles to technology diffusion may be related to the fact that the use of technology requires tacit knowledge which tends to move slowly between brains through a protracted process of imitation and repetition as occurs in learning by doing. Within communications clusters, there seems to be accelerated convergence. Obstacles to convergence in developing countries may be related to the paucity of social interactions between citizens of the same country

…From a policy perspective, the findings emphasize the fact that economic convergence requires intense social interaction, not just the presence of institutions of a certain quality. Regions that are formally part of the same nation-state but do not really interact with the more advanced parts of the country cannot expect to share similar development outcomes.(pg. 19).

Fascinating stuff.

Demographics & Inequality: 2015 Data

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Every year, economist Mark Perry draws on Census Bureau reports to paint of picture of the demographics of inequality. Looking at 2015 data, he constructed the following table:

incomeinequality

He concludes,

Household demographics, including the average number of earners per household and the marital status, age, and education of householders are all very highly correlated with household income. Specifically, high-income households have a greater average number of income-earners than households in lower-income quintiles, and individuals in high income households are far more likely than individuals in low-income households to be well-educated, married, working full-time, and in their prime earning years. In contrast, individuals in lower-income households are far more likely than their counterparts in higher-income households to be less-educated, working part-time, either very young (under 35 years) or very old (over 65 years), and living in single-parent households.

The good news is that the key demographic factors that explain differences in household income are not fixed over our lifetimes and are largely under our control (e.g. staying in school and graduating, getting and staying married, etc.), which means that individuals and households are not destined to remain in a single income quintile forever. Fortunately, studies that track people over time indicate that individuals and households move up and down the income quintiles over their lifetimes, as the key demographic variables highlighted above change, see C[arpe] D[iem] posts here, here and here.