Essays in applied microeconomics: The lottery winner survey, crime and social interactions, and why is there more crime in cities

Chapter One: The Lottery Winner Survey uses a natural experiment to measure the causal effect of income on labor supply. The data come from a recent survey of people who won the Massachusetts State Lottery. The Lottery provides a natural experiment in which some subjects are randomly assigned extra income and some are not. The data contain a "treatment" group of people who won the Lottery and a "control" group of people who did not. On average, the treatment people won {dollar}50,000 per year (pre-tax) for twenty years. I find a substantial treatment effect on labor supply. The treatment group has post-treatment labor income which is 30% lower than the control group. I measure the income elasticity of labor supply to be {dollar}-{dollar}.31 which is somewhat larger than what other researchers have found.; Chapter Two: The high variance of crime rates across time and space is one of the oldest puzzles in the social sciences (see Quetelet, 1835); this variance appears too high to be explained by changes in the exogenous costs and benefits of crime. We present a model where social interactions create enough covariance across individuals to explain the high cross-city variance of crime rates. This model provides an index of social interactions which suggests that the amount of social interactions is highest in petty crimes, moderate in more serious crimes and almost negligible in murder and rape.; Chapter Three: Crime rates are much higher in big cities than in either small cities or rural areas. 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 from crime in large cities can explain at most one quarter of the connection between city size and crime rates. Lower arrest probabilities, and lower probability of recognition are a feature of urban life, but these factors seem to explain at most one-fifth of the urban crime effect. Between one-third and one-half of the urban effect on crime can be explained by the presence of more female-headed households in cities. The small unexplained portion of the city size-crime connection may be related to omitted social variables.