Essays on semi-/non-parametric methods in econometrics

My dissertation contains three chapters focusing on semi-/non-parametric models in econometrics. The first chapter, which is a joint work with Sukjin Han, considers parametric/semiparametric estimation and inference in a class of bivariate threshold crossing models with dummy endogenous variables. We investigate the consequences of common practices employed by empirical researchers using this class of models, such as the specification of the joint distribution of the unobservables to be a bivariate normal distribution, resulting in a bivariate probit model. To address the problem of misspecification, we propose a semiparametric estimation framework with parametric copula and nonparametric marginal distributions. This specification is an attempt to ensure robustness while achieving point identification and efficient estimation. We establish asymptotic theory for the sieve maximum likelihood estimators that can be used to conduct inference on the individual structural parameters and the average treatment effects. Numerical studies suggest the sensitivity of parametric specification and the robustness of semiparametric estimation. This paper also shows that the absence of excluded instruments may result in the failure of identification, unlike what some practitioners believe. The second chapter develops nonparametric significance tests for quantile regression models with duration outcomes. It is common for empirical studies to specify models with many covariates to eliminate the omitted variable bias, even if some of them are potentially irrelevant. In the case where models are nonparametrically specified, such a practice results in the curse of dimensionality. I adopt the integrated conditional moment (ICM) approach, which was developed by Bierens (1982) and Bierens (1990) to construct test statistics. The proposed test statistics are functionals of a stochastic process which converges weakly to a centered Gaussian process. The test has non-trivial power against local alternatives at the parametric rate. A subsampling procedure is proposed to obtain critical values. The third chapter considers identification of treatment effect and its distribution under some distributional assumptions. I assume that a binary treatment is endogenously determined. The main identification objects are the quantile treatment effect and the distribution of the treatment effect. I construct a counterfactual model and apply Manski's approach (Manski (1990)) to find the quantile treatment effects. For the distribution of the treatment effect, I adapt the approach proposed by Fan and Park (2010). Some distributional assumptions called stochastic dominance are imposed on the model to tighten the bounds on the parameters of interest. It also provides confidence regions for identified sets that are pointwise consistent in level. An empirical study on the return to college confirms that the stochastic dominance assumptions improve the bounds on the distribution of the treatment effect.Economic

FloWaveNet : A Generative Flow for Raw Audio

Most modern text-to-speech architectures use a WaveNet vocoder for synthesizing high-fidelity waveform audio, but there have been limitations, such as high inference time, in its practical application due to its ancestral sampling scheme. The recently suggested Parallel WaveNet and ClariNet have achieved real-time audio synthesis capability by incorporating inverse autoregressive flow for parallel sampling. However, these approaches require a two-stage training pipeline with a well-trained teacher network and can only produce natural sound by using probability distillation along with auxiliary loss terms. We propose FloWaveNet, a flow-based generative model for raw audio synthesis. FloWaveNet requires only a single-stage training procedure and a single maximum likelihood loss, without any additional auxiliary terms, and it is inherently parallel due to the characteristics of generative flow. The model can efficiently sample raw audio in real-time, with clarity comparable to previous two-stage parallel models. The code and samples for all models, including our FloWaveNet, are publicly available.Comment: 9 pages, ICML'201

Time and Colin Clout: Pastoralism of Spenser's The Shepheardes Calender

Arcadia is a figment of the poet's imagination, a fiction to project the idea of perfection, or perfect otium. There is one exception, however, and it is that Arcadia, too, suffers from the limitation of time and that the Arcadians have a recurring sense of the everlasting presence of Death. The Renaissance sensibility wanted always to be reminded of the human temporal predicament, to see the skull under the face, as it were, and its writers were fond of quoting an anonymous speaker who averred his ubiquity by the well-known phrase, "Et in Arcadia ego", in which the speaker is, as Panofsky says, Death." "I, too, was in Arcadia" -if this was the 18th-century reception of the Baroque melancholy, turning it into a sweet yearning for the lost Arcadia, the truly Baroque sensibility had Death for its speaker triumphantly proclaiming "Even in Arcadia I am." The ineluctible passage of time destroys even Arcadia. Arcadia thus becomes an exemplum that temporality is the condition of human existence, an evidence of the inseparability of time from human experience

The impact of the Korean preliminary feasibility study on budgetary decisions

In 1999, Korea adopted the Preliminary Feasibility Study (PFS) to enhance fiscal efficiency by preventing unsuitable projects from being allocated a budget in the budget selection (BS) process. The PFS uses both economic and non-economic assessment criteria. However, according to data collected since the introduction of the PFS, about 30 per cent of projects not recommended for budget allocation received a budget. This raises questions about the relationship between the PFS and budget allocation. According to previous research, three issues about the effect of the PFS on budgetary decisions caused concern: the effect of PFS results on budgetary decisions, the appropriateness of the current PFS methodology, and the potential non-neutral behaviour of stakeholders taking part in the PFS. To deal with these, the thesis uses three key research questions: What is the impact of PFS results on budgetary decisions? Does the current PFS methodology lead to inappropriate decisions? And, lastly, what are the types of, extent of, and reasons for non-neutral behaviour by stakeholders in the PFS, and how might such behaviour be reduced? The study suggests that PFS results have a positive impact on budgetary decisions. The thesis also examines the appropriateness of the current PFS methodology and provides potential alternatives through both quantitative and qualitative analysis. Lastly, the thesis provides evidence of non-neutral behaviours by stakeholders in the PFS, which are categorized into four types: Promoter, Blocker, Dr. Pangloss, and Cassandra type. After this, this thesis examines the reasons for non-neutral behaviour and suggests possible policy alternatives for reducing non-neutral behaviour

The role of urban spatial structure in reducing VMT and GHG emissions

The aim of this study is to uncover the role of urban spatial structure in greenhouse gas (GHG) mitigation and to understand how sustainable urban form can better reduce climate change. Until now, a great number of studies have focused on the links between urban spatial structure and travel behavior, but little is known about spatial structure impacts on residential energy consumption. Most previous studies applied the use of neighborhood scale spatial structure to understand greenhouse gas emissions. However, such studies are too narrow to explain total urban spatial influences. This dissertation research therefore focuses on regional scale spatial structure (urban area level) in order to decrease GHGs and mitigate climate change. In doing so, this dissertation research consists of the three specific topics to scrutinize the role of sustainable urban spatial structure. The first topic (chapter 2) empirically examines whether and to what extent spatial structure affects the amount of household sector greenhouse gas emissions in U.S. urbanized areas. The study covers the comprehensive impacts of spatial structure not only on travel behavior, but also on residential energy consumption. Therefore, we can trace the overall impacts of urban spatial structure on all sources of GHG in the US household sector. The second topic (chapter 3) focuses on the impact of multiple geographic scales of sustainable built-environment to mitigate GHGs. In the study, the impacts of neighborhood level characters and regional level urban form elements are compared. The final topic (chapter 4) compares land-use policy with price policy to effectively reduce GHGs, and empirically shows how both policies can support GHG mitigation. 1) The influence of urban form on greenhouse emissions in the household sector This study comprehensively investigates the diverse paths through which urban form influences an individual household’s carbon dioxide emissions in the 125 largest urbanized areas in the U.S. This research takes a consolidated approach in investigating all energy consumption in the household sector: CO2 emissions from heating, cooling and transportation. The result of the multilevel structure equation model (multilevel SEM) analyses shows that doubling population-weighted density is associated with a reduction in CO2 emissions from household travel and residential energy consumption by 48% and 35%, respectively. The impacts of a centralized population and a polycentric structure have only a moderate impact in the analyses. The result also shows that doubling per capita transit subsidies is associated with a nearly 46% lower VMT and 18% reduction in transportation CO2 emissions. Given that household travel and residential energy use account for 42% of total U.S. carbon dioxide emissions, these research findings corroborate the notion that urban land use and transportation policies to build more compact and transit friendly cities should be a crucial part of any strategic efforts to mitigate GHG emissions and stabilize climate at all levels of government. 2) Sustainable urban form at local and regional scales The link between urban form and travel behavior is recognized as a key role in understanding the role of sustainable urban development in reducing greenhouse gas emissions in the transportation sector. Many recent studies have found that urban form variables—such as density, land use diversity, street design, destination accessibility, and distance to transit (the “5Ds”)—significantly influence travel behavior including mode choice, trip frequency, trip distance, and ultimately vehicle miles traveled (VMT), and they are regarded as the fundamental principles for land use policies to promote more sustainable transportation. In previous study, the 5 element impacts on VMT (VMT elasticity w.r.t. 5Ds) are significant, but not large. The reason seems to come from the small geographic unit of analysis (census tract, census block group or TAZ level). According to the NHTS (2009), more than 85% Americans still use automobile when they travel, and the average one-way trip distance by auto is about 9 miles, while the average radius of census tract and census block group is only about 0.5 and 0.3 miles, respectively. Moreover, many sustainable urban form studies have focuses on neighborhood character based on residence or working place, but home based work (HBW) is less than 10%, and there are various trip purposes, so there are diverse origins and destinations in each travel. Ironically, however, most studies suggest that coupling sustainable urban structure with supporting neighborhood structures decreases VMT, but most people use cars for travel for trips beyond the geographic unit of analysis. To fill the gap in the literature, this study investigates the influences of urban form at both geographical scales on travel behavior and carbon dioxide emissions using a multilevel analysis (3 level analysis; individual household, neighborhood, and urbanized area). The results show that the influence of regional level urban form is higher than that of neighborhood level on VMT. Regional level variables such as population weighted density (PWD), population centrality, jobs-to-housing ratio, and transit service supply significantly reduce VMT and CO2 from transportation sector. Most 5D elements at the neighborhood level also significantly diminish VMT and CO2, but the coefficient of regional level variables are higher than that of neighborhood level urban form elements. Moreover, the empirical outputs indicate that the positive effects of sustainable urban elements (5Ds) at the neighborhood level to reduce GHGs are increased under more high-density, high-centralized, and high job accessible UAs than auto-oriented UAs. For instance, when we double the compactness level at the neighborhood level, VMT decreases by about 50% in the average PWD UAs such as St. Louis. However, the influence can intensify by about 75% when the UA density (PWD) arrives at the New York level. 3) Complementarity between land use planning and pricing in VMT reduction To effectively reduce VMT, there seems to be no majority consensus. There is a wide gap between advocates of pricing policies and advocates of land use planning. Advocates of each approach underestimate the role and impacts of the other approach. In particular, skepticism still remains concerning the potential for more sustainable urban form and development patterns in reducing VMT and carbon emissions. The majority planners, on the other hand, emphasize that “getting prices right” policies cannot be effective in the absence of alternatives to automobile usage in many U.S. cities. However, land use planning and pricing approaches are complementary and potentially synergetic rather than competing and conflicting. Further, all possible policy options should be fully employed to achieve climate-stabilizing GHG reduction targets. Thus, policy analysts and decision makers should understand the complex interactions between various policy instruments to mitigate policy conflicts and maximize synergetic effects. Nonetheless, empirical research on the policy synergy between different approaches in transportation planning is extremely rare. To enhance the understanding of the policy synergy between pricing and land use planning approaches, this study examines the interaction effects between fuel prices and land use (urban form) variables in reducing VMT in 115 UAs for 10 years from Jan. 2002 to Dec. 2011 (monthly data). To find the both policy impacts, diverse empirical analyses are conducted from simple comparative analysis, to regression analysis, panel analysis, and panel type locally weighted smoothing (P-LOESS). The results show that there are synergic effect between land use policies and fuel price policies. Under the high fuel price, VMT reducing impacts of most compact urban form variables (UA level) are estimated to be stronger. When PWD doubles, VMT is reduced by about 19% under around 1 dollar per gallon ($2005), but the impact increases to about 27$2.5 /gallon. However, the complementary relations do not seem constant as gasoline price increases. With gasoline price increases, the elasticities of VMT dramatically increases below $2.5 per gallon. However, the elasticities remain at around 27$2.5 to $4 per gallon. The elasticities of urban compactness and centrality also show a similar pattern, in which they stabilize at a certain level. The implications of all findings from the three topics may greatly add to sustainable land use policy and transportation planning. While current federal- and state-level climate change policies mainly depend on technology solutions, the first study gives strong evidence for the importance of land use planning, as GHG mitigation strategies must alter travel behavior as well as energy consumption behavior. The comparison between local and regional level built environment impacts in the second topic highlight an essential issue of whether the state and/or regional governance can effectively reduce GHGs. The study shows that scattered and fragmented development of compact neighborhoods is not sufficient to moderate auto-oriented travel behavior. Instead, the study implies that strategic regional level coordination of smart growth policies can effectively foster sustainable travel behavior such as urban growth boundaries, balanced jobs-housing development, and transit oriented development. The final study underlines how both land use and fuel price policies generates synergic effects, which is largely overlooked by planners. The study empirically shows the adequate range of fuel prices to stimulate increasing effectiveness of sustainable land use policy, so the results can provide great evidence for the actual implementation of synergic activities

Optimal Pricing Effect on Equilibrium Behaviors of Delay-Sensitive Users in Cognitive Radio Networks

This paper studies price-based spectrum access control in cognitive radio networks, which characterizes network operators' service provisions to delay-sensitive secondary users (SUs) via pricing strategies. Based on the two paradigms of shared-use and exclusive-use dynamic spectrum access (DSA), we examine three network scenarios corresponding to three types of secondary markets. In the first monopoly market with one operator using opportunistic shared-use DSA, we study the operator's pricing effect on the equilibrium behaviors of self-optimizing SUs in a queueing system. %This queue represents the congestion of the multiple SUs sharing the operator's single \ON-\OFF channel that models the primary users (PUs) traffic. We provide a queueing delay analysis with the general distributions of the SU service time and PU traffic using the renewal theory. In terms of SUs, we show that there exists a unique Nash equilibrium in a non-cooperative game where SUs are players employing individual optimal strategies. We also provide a sufficient condition and iterative algorithms for equilibrium convergence. In terms of operators, two pricing mechanisms are proposed with different goals: revenue maximization and social welfare maximization. In the second monopoly market, an operator exploiting exclusive-use DSA has many channels that will be allocated separately to each entering SU. We also analyze the pricing effect on the equilibrium behaviors of the SUs and the revenue-optimal and socially-optimal pricing strategies of the operator in this market. In the third duopoly market, we study a price competition between two operators employing shared-use and exclusive-use DSA, respectively, as a two-stage Stackelberg game. Using a backward induction method, we show that there exists a unique equilibrium for this game and investigate the equilibrium convergence.Comment: 30 pages, one column, double spac