What Happens When We Randomly Assign Children to Families?

I use a new data set of Korean-American adoptees who, as infants, were randomly assigned to families in the U.S. I examine the treatment effects from being assigned to a high income family, a high education family or a family with four or more children. I calculate the transmission of income, education and health characteristics from adoptive parents to adoptees. I then compare these coefficients of transmission to the analogous coefficients for biological children in the same families, and to children raised by their biological parents in other data sets. Having a college educated mother increases an adoptee's probability of graduating from college by 7 percentage points, but raises a biological child's probability of graduating from college by 26 percentage points. In contrast, transmission of drinking and smoking behavior from parents to children is as strong for adoptees as for non-adoptees. For height, obesity, and income, transmission coefficients are significantly higher for non-adoptees than for adoptees. In this sample, sibling gender composition does not appear to affect adoptee outcomes nor does the mix of adoptee siblings versus biological siblings.

How Do Friendships Form?

We examine how people form social networks among their peers. We use a unique dataset that tells us the volume of email between any two people in the sample. The data are from students and recent graduates of Dartmouth College. First year students interact with peers in their immediate proximity and form long term friendships with a subset of these people. This result is consistent with a model in which the expected value of interacting with an unknown person is low (making traveling solely to meet new people unlikely), while the benefits from interacting with the same person repeatedly are high. Geographic proximity and race are greater determinants of social interaction than are common interests, majors, or family background. Two randomly chosen white students interact three times more often than do a black student and a white student. However, placing the black and white student in the same freshman dorm increases their frequency of interaction by a factor of three. A traditional "linear in group means" model of peer ability is only a reasonable approximation to the ability of actual peers chosen when we form the groups around all key factors including distance, race and cohort.

Colonialism and Modern Income -- Islands as Natural Experiments

Using a new database of islands throughout the Atlantic, Pacific and Indian Oceans we examine whether colonial origins affect modern economic outcomes. We argue that the nature of discovery and colonization of islands provides random variation in the length and type of colonial experience. We instrument for length of colonization using wind direction and wind speed. Wind patterns which mattered a great deal during the age of sail do not have a direct effect on GDP today, but do affect GDP via their historical impact on colonization. The number of years spent as a European colony is strongly positively related to the island's GDP per capita and negatively related to infant mortality. This basic relationship is also found to hold for a standard dataset of developing countries. We test whether this link is directly related to democratic institutions, trade, and the identity of the colonizing nation. While there is substantial variation in the history of democratic institutions across the islands, such variation does not predict income. Islands with significant export products during the colonial period are wealthier today, but this does not diminish the importance of colonial tenure. The timing of the colonial experience seems to matter. Time spent as a colony after 1700 is more beneficial to modern income than years before 1700, consistent with a change in the nature of colonial relationships over time.

The Determinants of Punishment: Deterrence, Incapacitation and Vengeance

Does the economic model of optimal punishment explain the variation in the sentencing of murderers? As the model predicts, we find that murderers with a high expected probability of recidivism receive longer sentences. Sentences are longest in murder types where apprehension rates are low, and where deterrence elasticities appear to be high. However, sentences respond to victim characteristics in a way that is hard to reconcile with optimal punishment. In particular, victim characteristics are important determinants of sentencing among vehicular homicides, where victims are basically random and where the optimal punishment model predicts that victim characteristics should be ignored. Among vehicular homicides, drivers who kill women get 56 percent longer sentences. Drivers who kill blacks get 53 percent shorter sentences.

The Social Consequences of Housing

The Social capital literature documents a connection between social connection and economic outcomes of interest ranging from government quality to economic growth. Popular authors suggest that housing and architecture are important determinants of social connection. This paper examines the connection between housing structure and social connection. We find that residents of large apartment buildings are more likely to be socially connected with their neighbors, perhaps because the distance between neighbors is lower in apartment buildings. Apartment residents are less involved in local politics, presumably because they are less connected with the public infrastructure and space that surrounds them. Street crime (robbery, auto theft) is also more common around big apartment buildings and we believe that this also occurs because of there is less connection between people in apartments and the streets that surround them.

The Response to Fines and Probability of Detection in a Series of Experiments

We use traffic data from a series of experiments in the United States and Israel to examine how illegal behavior is deterred by various penalty schemes and whether deterrence varies with age, income, driving record and criminal record. We find that red light running decreases sharply in response to an increase in the fine or an increase in the probability of being caught. The elasticity of violations with respect to the fine is larger for younger drivers and drivers with older cars. Drivers convicted of violent offenses or property offenses run more red lights on average but have the same elasticity as drivers without a criminal record. Within Israel, members of ethnic minority groups have the smallest elasticity with respect to a fine increase.

Aggregation Reversals and the Social Formation of Beliefs

In the past two elections, richer people were more likely to vote Republican while richer states were more likely to vote Democratic. This switch is an aggregation reversal, where an individual relationship, like income and Republicanism, is reversed at some level of aggregation. Aggregation reversals can occur when an independent variable impacts an outcome both directly and indirectly through a correlation with beliefs. For example, income increases the desire for low taxes but decreases belief in Republican social causes. If beliefs are learned socially, then aggregation can magnify the connection between the independent variable and beliefs, which can cause an aggregation reversal. We estimate the model's parameters for three examples of aggregation reversals, and show with these parameters that the model predicts the observed reversals.

Why Is There More Crime in Cities?

Crime rates are much higher in big cities than in either small cities or rural areas, and this situation has been relatively pervasive for several centuries. This paper attempts to explain this connection by using victimization data, evidence from the NLSY on criminal behavior and the Uniform Crime Reports. Higher pecuniary benefits for crime in large cities can explain approximately 27% of the effect for overall crime, though obviously much less of the urban- crime connection for non-pecuniary crimes such as rape or assault. Lower arrest probabilities, and lower probability of recognition, are a feature of urban life, but these factors seem to explain at most 20% of the urban crime effect. The remaining 45-60% of the effect can be related to observable characteristics of individuals and cities. The characteristics that seem most important are those that reflect tastes, social influences and family structure. Ultimately, we can say that the urban crime premium is associated with these characteristics, but we are left trying to explain why these characteristics are connected with urban living.

The Nature and Nurture of Economic Outcomes

The relative importance of biology and envi- ronment is one of the oldest and most prominent areas of scientific inquiry and has been exam- ined by researchers as diverse as David Hume (1748), Charles Darwin (1859), and Sigmund Freud (1930). Social scientists are particularly interested in the degree to which family and neighborhood environmental factors influence a child’s educational attainment and earnings. The stakes in this debate are quite high and far-reaching. As Richard Herrnstein and Charles Murray (1994) point out, the effectiveness of anti- poverty and pro-education policies is largely de- pendent on the degree to which environment matters. Any claim of treatment effects from dif- ferent family structures, different teachers, differ- ent peers, or different neighborhoods needs as a pre-condition that some aspects of environment are important to long-term outcomes. Attempts to understand the root causes of income inequality often involve trying to sort out the effects of family background from the effects of genetic endowments (see e.g., Zvi Griliches and William Mason, 1972; Christopher Jencks, 1972). In this paper I use data on adoptees to identify the causal effect from being adopted into a high-socioeconomic-status (SES) family versus a lower-SES family. I examine a range of out- comes including educational attainment, marital status, test scores, and the selectivity of college attended

Why Doesn't The US Have a European-Style Welfare State?

European countries are much more generous to the poor relative to the US level of generosity. Economic models suggest that redistribution is a function of the variance and skewness of the pre-tax income distribution, the volatility of income (perhaps because of trade shocks), the social costs of taxation and the expected income mobility of the median voter. None of these factors appear to explain the differences between the US and Europe. Instead, the differences appear to be the result of racial heterogeneity in the US and American political institutions. Racial animosity in the US makes redistribution to the poor, who are disproportionately black, unappealing to many voters. American political institutions limited the growth of a socialist party, and more generally limited the political power of the poor.