This study analyzes the wage and non-wage factors underlying non-metropolitan-to-metropolitan commuting decisions of households in five non-metropolitan counties in Northern Virginia. The potential fiscal and planning implications of these decisions are also discussed. Chapter one contains a description of the study area, problem statement and objectives. Chapter two reviews related literature on commuting, housing and job location, as well as rent and wage gradients. Chapter three provides a theoretical framework for analyzing household commuting decisions. Chapter four presents descriptive statistics, and introduces a switching regression system of equations to simultaneously estimate factors influencing commuting decisions and earnings in non-metropolitan and metropolitan labor markets. Chapter five reports the regression results, and simulates wage gaps and the distance of the metropolitan labor market draw for different groups of workers. Chapter six discusses potential fiscal implications of commuting and potential policies to manage growth in commuting. The empirical result shows that the major incentive for workers to commute is a large age gap between metropolitan and non-metropolitan labor market areas. Household responsibilities, housing preference and ability to find local jobs represent non-wage factors underlying commuting decisions. Two study findings suggest that the local fiscal implications of non-metropolitan-to-metropolitan commuting households may be limited. First, commuting households are found to have fewer school-aged children, and require less local expenditures on education. Second, commuting households are more likely to be homeowners, have more rooms in their homes, and provide a larger tax base. / Master of Science

The costs of acquiring parcels by condemnation are usually significantly higher than those for property acquired by negotiation, suggesting that Right-of-Way (R/W) acquisition costs may best be described by two different regression equations. This paper develops a switching regression model of acquisition cost to simultaneously predict the probability of whether a parcel will go to condemnation rather than be acquired via negotiation and the corresponding acquisition costs under these two regimes. The error terms of the selection equation and the two cost equations follow a trivariate normal distribution to reflect correlations across unobserved factors (such as a land owner's tenacity or a site's view value). When this model is calibrated using data on properties acquired across the state of Texas for transportation projects between 2008 and 2011, results suggest that R/W appraisers and staff should pay special attention to commercially used parcels in urban areas involving a partial taking with a relatively small remainder. Comparison of cost estimates between the two regimes (condemnation vs. negotiation) suggests that condemned parcels will have, on average, 78% higher acquisition costs across the 1,710 acquired properties and 51% greater price variation. These results suggest that it is much more costly to acquire a property and more difficult to accurately predict its costs if it cannot be acquired via negotiation. The application of model estimates to an example corridor highlights the value of simulation to capture all modeling uncertainties. This two-regime model is further extended to a three-category multinomial endogenous switching, allowing for differential cost estimates across negotiation-deed, administrative settlement, and condemnation contexts. A model of acquisition time -- from the agency's initial-offer date to its final possession date is also developed, to examine the effects of condemnation on acquisition duration. The results suggest that condemnation proceedings add approximately 7 to 8 months, on average, to parcel acquisitions by the Texas Department of Transportation. Taken together, such switching models for condemnation versus negotiated settlement highlight the benefits of avoiding condemnation proceedings in R/W acquisition. Estimation results illuminate the relative importance of various parcel and owner attributes, impacting the nature and cost of acquisition, and enhancing opportunities for R/W staff to identify more contentious properties and establish more reliable budget estimates. / text

Indiana University-Purdue University Indianapolis (IUPUI) / In this dissertation, I develop a regression-based approach to the specification and estimation of the effect of a presumed causal variable on a count-valued outcome of interest. Statistics for relevant causal inference are also derived. As an illustration and as a basis for comparing alternative parametric specifications with respect to ease of implementation, computational efficiency and statistical performance, the proposed models and estimation methods are used to analyze household fertility decisions. I estimate the effect of a counterfactually imposed additional year of wife’s education on actual family size (AFS) and desired family size (DFS) [count-valued variables]. In order to ensure the causal interpretability of the effect parameter as I define it, the underlying regression model is cast in a potential outcomes (PO) framework. The specification of the relevant data generating process (DGP) is also derived. The regression-based approach developed in the dissertation, in addition to taking explicit account of the fact that the outcome of interest is count-valued, is designed to account for potential sample selection bias due to a particular data deficiency in the count data context and to accommodate the possibility that some structural aspects of the model may vary with the value of a binary switching variable. Moreover, my approach loosens the equi-dispersion constraint [conditional mean (CM) equals conditional variance (CV)] that plagues conventional (poisson) count-outcome regression models. This is a particularly important feature of my model and method because in most contexts in empirical economics the data are either over-dispersed (CM < CV) or under-dispersed (CM > CV) – fertility models are usually characterized by the latter. Alternative count data models were discussed and compared using simulated and real data. The simulation results and estimation results using real data suggest that the estimated effects from my proposed models (models that loosen the equi-dispersion constraint, account for the sample selection, and accommodate variability in structural aspect of the models due to a switching variable) substantively differ from estimates from a conventional linear and count regression specifications.

The current study applies a two-state switching regression model to examine the behavior of a hypothetical portfolio of ten socially responsible (SRI) equity mutual funds during the expansion and contraction phases of US business cycles between April 1991 and June 2009, based on the Carhart four-factor model, using monthly data. The model identified a business cycle effect on the performance of SRI equity mutual funds. Fund returns were less volatile during expansion/peaks than during contraction/troughs, as indicated by the standard deviation of returns. During contraction/troughs, fund excess returns were explained by the differential in returns between small and large companies, the difference between the returns on stocks trading at high and low Book-to-Market Value, the market excess return over the risk-free rate, and fund objective. During contraction/troughs, smaller companies offered higher returns than larger companies (ci = 0.26, p = 0.01), undervalued stocks out-performed high growth stocks (hi = 0.39, p i = 0.01, p = 0.02). The hypothetical SRI portfolio was less risky than the market (bi = 0.74, p i = -0.01, p = 0.03). The hypothetical SRI portfolio exhibited similar risk as the market (bi = 0.93, p

This paper proposes the basic predictive regression and Markov Regime-Switching regression to predict the excess stock returns in both US and Sweden stock markets. The analysis shows that the Markov Regime-Switching regression models out perform the linear ones in out-of-sample forecasting, which is due to the fact that the regime-switching models capture the economic expansion and recession better.

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Submitted by Ana Luiza Neves de Holanda Barbosa (ana.barbosa@ipea.gov.br) on 2012-01-17T17:48:38Z No. of bitstreams: 2 tese_final_analuizaholanda.pdf: 1401652 bytes, checksum: fd6723241862cf776f8dcdc02a400af2 (MD5) tese_final_analuizaholanda.pdf: 1401652 bytes, checksum: fd6723241862cf776f8dcdc02a400af2 (MD5) / Approved for entry into archive by Andrea Virginio Machado (andrea.machado@fgv.br) on 2012-03-05T19:50:53Z (GMT) No. of bitstreams: 2 tese_final_analuizaholanda.pdf: 1401652 bytes, checksum: fd6723241862cf776f8dcdc02a400af2 (MD5) tese_final_analuizaholanda.pdf: 1401652 bytes, checksum: fd6723241862cf776f8dcdc02a400af2 (MD5) / Made available in DSpace on 2012-03-07T19:29:24Z (GMT). No. of bitstreams: 2 tese_final_analuizaholanda.pdf: 1401652 bytes, checksum: fd6723241862cf776f8dcdc02a400af2 (MD5) tese_final_analuizaholanda.pdf: 1401652 bytes, checksum: fd6723241862cf776f8dcdc02a400af2 (MD5) Previous issue date: 2011-09-12 / This study investigates the wage gap between the public and private sectors in Brazil. The analysis is carried out with 2009 microdata from the Pesquisa Nacional por Amostra de Domicílios (PNAD) and it takes account its complex sample design. The main contribution of this study is the estimation of a switching endogenous regression model that corrects the selection bias in the choice of employment sector. This model allows for the identification of some factors that determine the entrance of the individual in the public sector labor market. The public-private wage gap is calculated by gender as labor supply varies significantly between women and men. The results show that public sector wages are higher than those in the private sector. In particular, the public-private wage gap for women is higher than for men. / A presente tese engloba três artigos sobre diferencial de salários e estimação de demanda no Brasil. O primeiro artigo investiga o diferencial de salários entre os trabalhadores dos setores público e privado. A principal contribuição deste estudo é a estimação de um modelo de regressão com mudança endógena (endogenous switching regression model), que corrige o viés de seleção no processo de escolha setorial realizada pelos trabalhadores e permite a identificação de fatores determinantes na entrada do trabalhador no mercado de trabalho do setor público. O objetivo do segundo trabalho é calcular a elasticidade-preço e a elasticidade-despesa de 25 produtos alimentares das famílias residentes nas áreas rurais e urbanas do Brasil. Para tanto, foram estimados dois sistemas de equações de demanda por alimentos, um referente às famílias residentes nas áreas rurais do país e o outro sistema associado às famílias residentes nas áreas urbanas. O terceiro artigo busca testar a validade do modelo unitário para solteiros(as) e a validade do modelo de racionalidade coletiva de Browning e Chiappori (1998) para casais no Brasil. Para tanto, foi estimado um sistema de demanda do consumo brasileiro com base no modelo QUAIDS, que apresenta uma estrutura de preferências flexível o suficiente para permitir curvas de Engel quadráticas.