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Estimation of Treatment Effects Using Regression Discontinuity Design

Rahman, Mohammad Mahbubur

[Thesis]. Manchester, UK: The University of Manchester; 2014.

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Abstract

This thesis includes three substantive empirical studies (in Chapters 3, 4 and 5),where each study uses the same econometric methodology, named Regression Discontinuitydesign, which has an attractive feature – local randomisation. This feature has giventhe superiority of the method over the other evaluation methods in estimating unbiasedtreatment effects. Besides, the fuzzy Regression Discontinuity design can control for theendogeneity of the treatment variable, which is another advantage of the method. In eachof the studies considered, the endogeneity problem exists. The application of the fuzzyRegression Discontinuity design is itself a contribution in each of the studies. Moreover,each study contributes in its own field.In Chapter 3, we investigate how much the Social Safety Net programs, that providefree food, or cash, or both to the food insecure households in Bangladesh, improve calorieconsumption of the beneficiary households. Using Household Income and ExpenditureSurvey 2005, we find that the effect of the programs is around 843 kilo calorie, which issubstantial compared to the previous studies.In Chapter 4, we examine how much was the impact of Education Maintenance Allowance,a program that provided weekly allowance to the young people in Years 12 and13 in England, on the staying rate in the post compulsory full-time education. The programwas abolished in 2010. Using the Longitudinal Survey of Young People in England,we find that the effect of the program was substantial – around 15 percent. The effect ofan £1 increase in weekly allowance was around 1 percent. These effects were mainly onthe white young people.Using the household survey data – Family Expenditure Survey (1968-2009) – inUK, Chapter 5 establishes that before 1981 consumption substantially fell at the retirementage. This fall is less severe after 1980. However, throughout the data period, consumptionfall at the retirement age is fully explained by the expected fall in income, whichcontradicts the life cycle model, where a consumption growth is independent of an incomegrowth.