Economic Development of Urban Areas

In this dissertation I study the development of urban areas. At the aggregate level I investigate how they may be affected by climate change policies and by being designated the seat of governmental power. At the household level I study with coauthors how microfinance could improve the health of urban residents. In Chapter 1, I investigate how local employment may be affected by electricity price increases, which is a likely consequence of climate change policies. I outline how previous studies that find large, negative effects may be biased. To overcome these biases I develop a novel estimation strategy that blends border-pair regressions with the synthetic control methodology. I show the conditions for consistent estimation. Using this estimator, I find no effect of contemporaneous price changes on employment. Consistent with the longer time-frame for manufacturing decisions, I do find evidence for negative effects from perceived permanent price shocks. These estimates are much smaller than previous research has found. National capital cities are often substantially larger than other cities in their countries. In Chapter 2, I investigate whether there is a causal effect from being a capital by studying the 1960 relocation of the Brazilian capital from Rio de Janeiro to Brasília. Using a synthetic controls strategy I find that losing the capital had no significant effects on Rio de Janeiro in terms of population, employment, or gross domestic product (GDP). I find that Brasília experienced large and significant increases in population, employment, and GDP. I find evidence of large spillovers from the public to the private sector. Chapter 3 investigates how microfinance could increase the uptake of costly health goods. We study the effect of time payments (micro-loans or micro-savings) on willingness-to-pay (WTP) for a water filter among households in the slums of Dhaka, Bangladesh. We find that time payments significantly increase WTP: compared to a lump-sum up-front purchase, median WTP increases 83% with a six-month loan and 115% with a 12-month loan. We find that households are quite patient with respect to consumption of health inputs. We find evidence for the presence of credit and savings constraints.

Motion Planning and Controls with Safety and Temporal Constraints

Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.