On the distributional effects of income in an aggregate consumption relation

Abstract .  In this paper we analyse the influence of characteristics of the income distribution in modelling aggregate consumption expenditure. We model the aggregate consumption relation of a heterogeneous population, using a statistical distributional approach of aggregation, and apply it to UK-Family Expenditure Survey data. A bootstrap test based on a non-parametric estimation methodology, which accounts for the presence of continuous and discrete variables, suggests that the mean and the dispersion of the income distribution significantly influence aggregate consumption expenditure. Also, the parameters of the aggregate relation are time varying. These findings have implications for constructing empirically sound models of aggregate consumption expenditure.     

Media Coverage and the Stock Market Valuation of TARP Participating Banks‡

We examine the impact of media coverage of the Capital Purchase Program (CPP) under the Troubled Assets Relief Program on the equity market valuation of participating bank holding companies (CPP banks). We document substantial negative coverage of the CPP and its participants over the five quarters following the program's initiation. We find that the extent of negative media coverage about the CPP exerted substantial downward pressure on the stock returns of CPP banks, decreasing their valuation relative to bank holding companies not participating in the program. We show that our findings cannot be explained by differences in the banks’ financial viability at the CPP's initiation, new information about their performance being released to the market after the CPP's initiation or preceding stock returns causing the negative media coverage. Our findings highlight the importance of investor sentiment, as reflected by the tone of media coverage, in banks’ valuation during a period of high uncertainty in financial markets.     

The Rights of Employees with Disabilities: Supreme Court Interpretations of the Americans with Disabilities Act and Their Implications for Human Resource Management

The Americans With Disabilites Act (ADA) of 1990 provides broad protection to an estimated 43 million Americans against discrimination in many facets of their lives. Title I of the Act prohibits discrimination in employment. Title III of the Act, which prohibits discrimination in public accommodation, has also impacted the employment relationship. Eight years after the passage of the Act, the U.S. Supreme Court issued its first ruling under the ADA. Two subsequent decisions have been rendered that further interpret the statute and the Court has repeatedly denied to review cases that deal with another key interpretation of the ADA. This paper analyzes these cases and decisions and their implications for management practices.     

What is a strategic acquisition? Decision modeling in support of foreclosed housing redevelopment

This paper describes and develops a model for calculating location-based strategic values of foreclosed properties considered for acquisition and redevelopment by community development corporations (CDCs). A property’s strategic value refers to its proximity to site-specific neighborhood amenities and disamenities (e.g. schools, public transit, distressed properties), given the relative importance of that proximity to CDC organizational and community objectives. We operationalize the concept of strategic value, and apply this concept to a salient public sector decision problem. Using data and value assessments from a CDC engaged in foreclosed housing redevelopment, we compute measures of strategic value for a set of acquisition candidates. We show that strategic values can differ in systematic ways depending on the types of amenities and disamenities identified as relevant for CDC acquisition decisions, the relative importance assigned to those amenities and disamenities, and the utility maximization objectives of the CDC. We conclude by proposing a multi-criteria decision model for foreclosed housing acquisition and redevelopment which incorporates a theory of residential housing impacts for which strategic value measures are a special case.     

Why and how to use vector autoregressive models for quality control: the guideline and procedures

While quality control on multivariate and serially correlated processes has attracted research attentions, a number of very detailed problems need to be overcome in order to construct practical control charts. We suggest guidelines for construction of control charts based on vector autoregressive (VAR) residuals. We discuss why VAR model is reasonable for real processes in nature, the use of VAR models to approximate multivariate serially correlated processes, residual estimation, selecting the number of variables, and selecting appropriate orders, among other issues. In addition, we illustrate an example employing VAR techniques to approximate a multivariate process previously examined and construct a control chart to monitor residuals. Last, we illustrate the potential development and use of the VAR residual chart to assist quality control and improvement.     

Estimating panel data models in the presence of endogeneity and selection

We consider estimation of panel data models with sample selection when the equation of interest contains endogenous explanatory variables as well as unobserved heterogeneity. Assuming that appropriate instruments are available, we propose several tests for selection bias and two estimation procedures that correct for selection in the presence of endogenous regressors. The tests are based on the fixed effects two-stage least squares estimator, thereby permitting arbitrary correlation between unobserved heterogeneity and explanatory variables. The first correction procedure is parametric and is valid under the assumption that the errors in the selection equation are normally distributed. The second procedure estimates the model parameters semiparametrically using series estimators. In the proposed testing and correction procedures, the error terms may be heterogeneously distributed and serially dependent in both selection and primary equations. Because these methods allow for a rather flexible structure of the error variance and do not impose any nonstandard assumptions on the conditional distributions of explanatory variables, they provide a useful alternative to the existing approaches presented in the literature.     

Quasi-maximum likelihood estimation and testing for nonlinear models with endogenous explanatory variables

I propose a quasi-maximum likelihood framework for estimating nonlinear models with continuous or discrete endogenous explanatory variables. Joint and two-step estimation procedures are considered. The joint procedure is a quasi-limited information maximum likelihood procedure, as one or both of the log likelihoods may be misspecified. The two-step control function approach is computationally simple and leads to straightforward tests of endogeneity. In the case of discrete endogenous explanatory variables, I argue that the control function approach can be applied with generalized residuals to obtain average partial effects. I show how the results apply to nonlinear models for fractional and nonnegative responses.     

Public Open Access and Private Timber Harvests: Theory and Application to the Effects of Trade Liberalization in Mexico

A common popular assertion is that trade liberalization encourages deforestation. But whether this is true depends on how trade policies affect the allocation of land among competing uses and how they influence illegal cutting of public forests. A model is presented that allows for forests to be either public or private, and public forests are divided into protected (or managed) and threatened categories. Effects of price changes are shown on each part of the forest. An empirical version of the model is applied to the case of Mexico with NAFTA. Most scenarios considered show that NAFTA will have positive long-run effects on forest cover in Mexico but that this is net of losses on private lands.     

Major bleeding risk and healthcare economic outcomes of non-valvular atrial fibrillation patients newly-initiated with oral anticoagulant therapy in the real-world setting

Aims: This study compared the risk for major bleeding (MB) and healthcare economic outcomes of patients with non-valvular atrial fibrillation (NVAF) after initiating treatment with apixaban vs rivaroxaban, dabigatran, or warfarin.

Methods: NVAF patients who initiated apixaban, rivaroxaban, dabigatran, or warfarin were identified from the IMS Pharmetrics Plus database (January 1, 2013–September 30, 2015). Propensity score matching (PSM) was used to balance differences in patient characteristics between study cohorts: patients treated with apixaban vs rivaroxaban, apixaban vs dabigatran, and apixaban vs warfarin. Risk of hospitalization and healthcare costs (all-cause and MB-related) were compared between matched cohorts during the follow-up.

Results: During the follow-up, risks for all-cause (hazard ratio [HR]?=?1.44, 95% confidence interval [CI]?=?1.2–1.7) and MB-related (HR?=?1.57, 95% CI?=?1.0–2.4) hospitalizations were significantly greater for patients treated with rivaroxaban vs apixaban. Adjusted total all-cause healthcare costs were significantly lower for patients treated with apixaban vs rivaroxaban ($3,950 vs $4,333 per patient per month [PPPM], p?=?.002) and MB-related medical costs were not statistically significantly different ($100 vs $233 PPPM, p?=?.096). Risk for all-cause hospitalization (HR?=?1.98, 95% CI?=?1.6–2.4) was significantly greater for patients treated with dabigatran vs apixaban, although total all-cause healthcare costs were not statistically different. Risks for all-cause (HR?=?2.22, 95% CI?=?1.9–2.5) and MB-related (HR?=?2.05, 95% CI?=?1.4–3.0) hospitalizations were significantly greater for patients treated with warfarin vs apixaban. Total all-cause healthcare costs ($3,919 vs $4,177 PPPM, p?=?.025) and MB-related medical costs ($96 vs $212 PPPM, p?=?.026) were significantly lower for patients treated with apixaban vs warfarin.

Limitations: This retrospective database analysis does not establish causation.

Conclusions: In the real-world setting, compared with rivaroxaban and warfarin, apixaban is associated with reduced risk of hospitalization and lower healthcare costs. Compared with dabigatran, apixaban is associated with lower risk of hospitalizations.     

Airport infrastructure spillovers in a network system

Airports in the US air transport network have become increasingly congested, leading to delays for business travelers and freight shipments. Since disruptions in one part of the network exacerbate problems throughout the system, airport infrastructure expansions to enhance air traffic flows confer travel-time savings and reliability benefits, and thus increased worker productivity and shipping efficiency for manufacturing firms. We evaluate such spillovers, and find that higher own-state airport infrastructure implies lower manufacturing costs from both labor- and materials-savings. Airport expansion in connected states has a comparable effect for states with hub airports, and an even greater impact for other states.