No-notice incidents occur with no advance notice of time and place. Family members may be separated when a no-notice incident strikes during the daytime. They may seek to gather the household members first and evacuate as a unit, and parents may head in the "wrong" direction to pick up their children from schools/daycare centers. Many previous studies have acknowledged that such behavior exists but few, if any, have examined it in-depth. Additionally, this behavior has rarely been integrated with transportation simulation models of evacuation conditions. As shown through this work, such omissions generate overly optimistic network performance. Acknowledging the behavior also leads to potential network improvements by moving dependents (people being picked up by other household members) to more accessible locations. This study investigated no-notice evacuation household gathering behavior based on 315 interviews conducted in the Chicago metropolitan area, in which interviewees were asked about their evacuation and logistic decisions. The study analyzed household pick-up and gathering behavior from the interviews, developed models to represent the behavior, and integrated the household behavior models with network simulation modeling to examine the effects of household behaviors on network evacuation performance. Logistic regression models were built to predict the probability that parents retrieve children from school in normal and emergency situations. Gender, car availability, and travel distance (between parents and children) were the main influencing factors to determining child-chauffeuring travel behavior, where gender difference appeared to be most prominent. Women are more responsible for picking up children from school than men, and both women and men are more likely to pick up children under emergency conditions compared to a normal situation. A complex model to integrating human behavior analysis and network assignment modeling was presented in this study. The model follows the traditional four step urban transportation planning process and 1) estimates household gathering chains in an evacuation using a discrete choice (Logit) model and sequences chains following the principle of "nearest first", 2) assigns directions of destinations ensuring the least travel time to safe zones from the last stop within the hot zones, 3) applies decision tree based mode choice models to determine the mode used for evacuation, and 4) uses a dynamic assignment method to assign time-varying demand to the network. The whole framework was tested in the Chicago metropolitan region for two hypothetical incidents, one causing a 5-mile evacuation radius and the other a 25-mile radius evacuation. The results showed that considering household gathering behavior will reduce proportions of evacuees who reach safe zones by a certain time period, while not necessarily deteriorating overall network traffic performance. To facilitate the chain-based evacuations, a relocation model is proposed by moving carless dependents of facilities (such as schools and daycare centers) to more accessible locations for pickup; a linear integer program is presented to determine optimal sites. The optimization model uses estimated travel time obtained from a micro-simulation model and a procedure is presented to iterate between the two models (optimization and simulation). The methodology was applied to a sample network based on Chicago Heights, Illinois. The sample application involved four facilities with 780 dependents and three safe time thresholds, i.e., 30, 45 and 60 minutes. The sample application tested two scenarios - no mode shift and mode shift from car to bus - and introduced average speed and the number of successful evacuations of dependents to evaluate the performance of a relocation strategy. The safe evacuation time threshold was quite important for the relocation strategy; when it is adequate, relocating dependents benefits both those picking up dependents and the other vehicles in the network. This dissertation contributes to the fields of evacuation modeling and transportation engineering, in general. This study investigates child pick-up, spouse gathering, and home gathering behavior during hypothetical incidents, and identifies characteristics associated with household decision makers that influence this behavior. The study also presents a model to integrate the behavior with road network simulation modeling; the combined model could be used to investigate the effects of gathering behavior on network traffic performance and identify potential spatial and temporal bottlenecks. Finally, this work explored a strategy to facilitate household pick up chains by relocating facility dependents to more accessible site. The study can support any city evacuation plan development. / Ph. D.

This dissertation investigates the evacuees' behavior under hurricane evacuation conditions and develops an agent-based travel demand model system for hurricane evacuation simulation using these behavioral findings. The dissertation econometrically models several important evacuation decisions including evacuate-stay, accommodation type choice, evacuation destination choice, evacuation mode choice, departure time choice, and vehicle usage choice. In addition, it explicitly considers the pre-evacuation preparation activities using activity-based approach. The models are then integrated into a two-module agent-based travel demand model system. The dissertation first develops the evacuate-stay choice model using the random-coefficient binary logit specification. It uses heterogeneous mean of the random parameter across households to capture shadow evacuation. It is found that the likelihood of evacuation for households that do not receive any evacuation notice decreases as their distance to coast increase on average. The distance sensitivity factor, or DSF, is introduced to construct the different scenarios of geographical extent of shadow evacuation. The dissertation then conducts statistical analysis of the vehicle usage choice. It identifies the contributing factors to households' choice of the number of vehicles used for evacuation and develop predictive models of this choice that explicitly consider the constraint imposed by the number of vehicles owned by the household. This constraint is not accommodated by ordered response models. Data comes from a post-storm survey for Hurricane Ivan. The two models developed are variants of the regular Poisson regression model: the Poisson model with exposure and right-censored Poisson regression. The right-censored Poisson model is preferred due to its inherent capabilities, better fit to the data, and superior predictive power. The multivariable model and individual variable analyses are used to investigate seven hypotheses. Households traveling longer distances or evacuating later are more likely to use fewer vehicles. Households with prior hurricane experience, greater numbers of household members between 18 and 80, and pet owners are more likely to use a greater number of vehicles. Income and distance from the coast are insignificant in the multivariable models, although their individual effects have statistically significant linear relationship. However, the Poisson based models are non-linear. The method for using the right-censored Poisson model for producing the desired share of vehicle usage is also provided for the purpose of generating individual predictions for simulation. The dissertation then presents a descriptive analysis of and econometric models for households' pre-evacuation activities based on behavioral intention data collected for Miami Beach, Florida. The descriptive analysis shows that shopping - particularly food, gasoline, medicine, and cash withdrawal - accounts for the majority of preparation activities, highlighting the importance of maintaining a supply of these items. More than 90% of the tours are conducted by driving, emphasizing the need to incorporate pre-evacuation activity travel into simulation studies. Households perform their preparation activities early in a temporally concentrated manner and generally make the tours during daylight. Households with college graduates, larger households, and households who drive their own vehicles are more likely to engage in activities that require travel. The number of household members older than 64 has a negative impact upon engaging in out-of-home activities. An action day choice model for the first tour suggests that households are more likely to buy medicine early but are more likely to pick up friends/relatives late. Households evacuating late are more likely to conduct their activities late. Households with multiple tours tend to make their first tour early. About 10% of households chain their single activity chains with their ultimate evacuation trips. The outcomes of this paper can be used in demand generation for traffic simulations. The dissertation finally uses the behavioral findings and develops an agent-based travel demand model system for hurricane evacuation simulation, which is capable of generating the comprehensive household activity-travel plans. The system implements econometric and statistical models that represent travel and decision-making behavior throughout the evacuation process. The system considers six typical evacuation decisions: evacuate-stay, accommodation type choice, evacuation destination choice, mode choice, vehicle usage choice and departure time choice. It explicitly captures the shadow evacuation population. In addition, the model system captures the pre-evacuation preparation activities using an activity-based approach. A demonstration study that predicts activity-travel patterns using model parameters estimated for the Miami-Dade area is discussed. The simulation results clearly indicate the model system produced the distribution of choice patterns that is consistent with sample observations and existing literature. The model system also identifies the proportion of the shadow evacuation population and their geographical extent. About 23% of the population outside the designated evacuation zone would evacuate. The shadow evacuation demand is mainly located within 3.1 miles (5 km) of the coastline. The output demand of the model system works with agent-based traffic simulation tools and conventional trip-based simulation tools. The agent-based travel demand model system is capable of generating activity plans that works with agent-based traffic simulation tools and conventional trip-based simulation tools. It will facilitate the hurricane evacuation management. / Ph. D.

Thesis advisor: Peter Gottschalk / Thesis advisor: Shannon Seitz / This dissertation contains two essays in labor economics. It provides a descriptive analysis on income volatility and develops a microeconomic model to study how married couples make joint decisions in response to such income volatility. The first essay examines the recent trends in household income volatility in the United States, West Germany and Great Britain, and compares household income volatility with individual income volatility. I estimate a formal error components model using the Cross-national Equivalence File from 1979 to 2004. I find that household income volatility, measured by the transitory variance of household income, accounts for more than half of the total income variance for all three countries. Despite the differences in the total household income variances among the three countries, the permanent variances converges since the late 1990s. The household earnings volatility is always lower than the individual earnings volatility for married couples, which suggests some evidence of intra-household insurance. In the second essay I examine whether married couples make joint labor supply decisions in response to each other's wage shocks. The study of this question aids in understanding the link between the recent rise in earnings volatility and household joint decisions. I develop an intra-household insurance model based on the collective framework, which allows for insurance against both permanent and transitory wage shocks from both partners. Estimation using Survey of Income and Program Participation shows that individuals increase labor supply in response to spouse's adverse wage shocks and such labor supply responses are larger when shocks are permanent than transitory. A household makes less transfer to the individual with more volatile income, which can be considered as a price for insurance.This intra-household insurance reduces earnings volatility by about 1.2% to 7.7%. These results suggest that joint labor supply decisions provide a smoothing effect on shocks to earnings and household income. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

<p>The essays in applied microeconomics contained within this dissertation examine prices in the developing economy contexts of Indonesia and the Philippines. Prices, observed and unobserved, are determined by and incentivize the behavior of all agents in the economy. Prices describe the interaction of individuals within a household and households within a market and reveal traits critical for development. Traits such as the efficiency of household resource allocations and the completeness of markets are analyzed in Central Java, Indonesia using a rich, longitudinal survey containing detailed price data used to estimate household demand systems. Unobserved, implicit prices of environmental goods are analyzed in the context of the Philippines. The valuation of environmental quality's implicit price is illustrated by comparing the health and human capital outcomes of the highly and least exposed. Exposure to environmental toxins can produce short and long-term damages to health and human capital reflecting undervaluation of the implicit price of environmental quality. The combined results of these essays on prices in development economics reveal allocation inefficiencies within the household and the economy and provide direction for development policy around the world.</p> / Dissertation

Many children in developing countries forgo education due to the direct or opportunity costs of attending school. To help defray the direct costs of secondary schooling, the Ghanaian government launched its free secondary school initiative in 2017, which sought to make tuition and all educational-related expenses free for every Ghanaian child who passed the Basic Education Certificate Examination (BECE). The first objective of this study is to examine to what extent the association between household income and school enrollment decreased in strength over time due to Ghana’s 2017 policy reform using the Ghana socio-economic panel survey (GSPS) and difference-in-differences estimation technique. Our results show that household assets (a proxy for income) had a significant and positive association with school enrollment before the policy change; however, household assets have no significant association with enrollment after the policy change, thus suggesting that family resources do not matter for child enrollment after the policy change. Our results also imply that the 2017 policy reform effectively reduced the hurdles facing lower-income families in paying for secondary school education. The second objective of this study is to examine the effects of this government policy on household labor market outcomes in Ghana. Using the Ghana Socio-Economic Panel Survey (GSPS) and the difference-in-differences estimation technique, we found an increase in labor supply and wages for households with SHS kids before the policy change; however, after policy reform, both labor supply and wages of SHS households decreased suggesting that the free SHS policy did eliminates the direct cost of schooling. These results also indicate that the free SHS policy has significant implications for human capital development and household welfare and health since the policy eliminates the direct cost of schooling. The third chapter examines the impact of environmental tax revenues on domestic healthcare expenditures using panel data of 96 developing and developed countries from 2000 to 2018 and the fixed effect estimation technique. We find a positive and statistically significant association between total environmental tax revenue and government health expenditures; however, this finding is primarily driven by low-income countries. In addition, we find a positive effect of all kinds of environmental tax revenues on government health expenditures; however, the largest and strongest effect arises with pollution tax and transport tax respectively. Our empirical results confirm the validity of the double dividend hypothesis, thus suggesting that environmental tax revenues have significant implications for public health expenditures.

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This PhD dissertation represents an effort to understand individual behavior leading to decisions regarding natural resource use and compliance with conservation policy at the government and at the community levels through the analysis of specific cases in the Brazilian Amazon. I first analyze the case of smallholder land clearing along the Transamazon and BR-163 highways in the face of Brazilian Forest Code enforcement by the federal government. My hypothesis is that smallholder land clearing paths over time are affected by assessments of the probability of being caught violating the Forest Code. I develop a dynamic decision model that considers the potential benefits and costs accrued from land clearing through time by a representative smallholder and include her perception of the probability of Forest Code enforcement, unobserved to the researcher. I apply an endogenous switching regressions econometric model to data collected with a sample of 542 households in 2003 and 2013/14. I find that longer land tenure frontiers where there are opportunities for smallholders to transition to cattle grazing from agriculture deserve the attention of enforcement of land clearing laws and restrictions and that the use of the forest by a smallholder is a protective signal that must be considered and encouraged. My results suggest that alleged government efforts to enforce the Forest Code among smallholders in the sample region have been ineffective. The second case I analyze is that of fisher households that enforce community fishing agreements, known as accords, in the floodplains of the Amazon River surrounding the city of Santarém. My hypothesis is that individual households benefit from their own fishing accords enforcement effort through fishing time savings. A factor demand analysis applied to data collected with over 600 households reveals that statistically important drivers of labor demand and fuel include the level of dedication of a household and its history in implementing fishing accords, the landscape, the flood cycle, the distance to the main regional market and biomass. The average household fishing time savings from enforcing accords range between 59 and 36 eight-hour days for a six-month-period, an important argument for continuing the enterprise. / PHD

Submitted by Luiza Gueller Zardin (luizazardin@gmail.com) on 2016-06-07T13:14:35Z No. of bitstreams: 1 dissertacao_luiza_templatebmhs.pdf: 408467 bytes, checksum: 73263bbe753eda7c5a71fd95f23893b7 (MD5) / Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2016-06-08T15:11:55Z (GMT) No. of bitstreams: 1 dissertacao_luiza_templatebmhs.pdf: 408467 bytes, checksum: 73263bbe753eda7c5a71fd95f23893b7 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2016-06-13T17:33:28Z (GMT) No. of bitstreams: 1 dissertacao_luiza_templatebmhs.pdf: 408467 bytes, checksum: 73263bbe753eda7c5a71fd95f23893b7 (MD5) / Made available in DSpace on 2016-06-13T17:35:54Z (GMT). No. of bitstreams: 1 dissertacao_luiza_templatebmhs.pdf: 408467 bytes, checksum: 73263bbe753eda7c5a71fd95f23893b7 (MD5) Previous issue date: 2016-03-22 / We construct a frictionless matching model of the marriage market where women have bidimensional attributes, one continuous (income) and the other dichotomous (home ability). Equilibrium in the marriage market determines intrahousehold allocation of resources and female labor participation. Our model is able to predict partial non-assortative matching, with rich men marrying women with low income but high home ability. We then perform numerical exercises to evaluate the impacts of income taxes in individual welfare and find that there is considerable divergence in the female labor participation response to taxes between the short run and the long run.

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Paper [I] Using a unique and highly detailed data set on energy consumption at the appliance-level for 200 Swedish households, seemingly unrelated regression (SUR)-based end-use specific load curves are estimated. The estimated load curves are then used to explore possible restrictions on load shifting (e.g. the office hours schedule) as well as the cost implications of different load shift patterns. The cost implications of shifting load from "expensive" to "cheap" hours, using the Nord Pool spot prices as a proxy for a dynamic price, are computed to be very small; roughly 2-4% reduction in total daily costs from shifting load up to five hours ahead, indicating small incentives for households (and retailers) to adopt dynamic pricing of electricity. Paper [II] Using a detailed data set on appliance-level electricity consumption at the hourly level, we provide the first estimates of hourly and end-use-specific income elasticities for electricity. Such estimates are informative about how consumption patterns in general, and peak demand in particular, will develop as households’ income changes. We find that the income elasticities are highest during peak hours for kitchen and lighting, with point estimates of roughly 0.4, but insignificant for space heating. Paper [III] In this paper, I estimate the price elasticity of electricity as a function of the choice between fixed-price and variable-price contracts. Further, assuming that households have imperfect information about electricity prices and usage, I explore how media coverage of electricity prices affects electricity demand, both by augmenting price responsiveness and as a direct effect of media coverage on electricity demand, independent of prices. I also address the endogeneity of the choice of electricity contract. The parameters in the model are estimated using unique and detailed Swedish panel data on monthly household-level electricity consumption. I find that price elasticities range between −0.025 and −0.07 at the mean level of media coverage, depending on contract choice, and that households with monthly variation in electricity prices respond more to prices when there is extensive media coverage of electricity prices. When media coverage is high, for example 840 news articles per month (which corresponds to the mean plus two standard deviations), the price elasticity is −0.12, or 1.7 times the elasticity at the mean media coverage. Similarly, media coverage is also found to have a direct effect on electricity demand. Paper [IV] I explore how households switch between fixed-price and variable-price electricity contracts in response to variations in price and temperature, conditional on previous contract choice. Using panel data with roughly 54000 Swedish households, a dynamic probit model is estimated. The results suggest that the choice of contract exhibits substantial state dependence, with an estimated marginal effect of previous contractchoiceof0.96, andthattheeffectofvariationinpricesandtemperatureonthechoice of electricity contract is small. Further, the state dependence and price responsiveness are similar across housing types, income levels and other dimensions. A plausible explanation of these results is that transaction costs are larger than the relatively small cost savings from switching between contracts.