Viewpoint: Estimating the causal effects of policies and programs

Estimation, inference and interpretation of the causal effects of programs and policies have all advanced dramatically over the past 25 years. We highlight three particularly important intellectual trends: an improved appreciation of the substantive importance of heterogeneous responses and of their methodological implications, a stronger focus on internal validity brought about by the “credibility revolution,” and the scientific value that follows from grounding estimation and interpretation in economic theory. We discuss a menu of commonly employed partial equilibrium approaches to the identification of causal effects, emphasizing that the researcher's central intellectual contribution always consists of making an explicit case for a specific causal interpretation given the relevant economic theory, the data, the institutional context and the economic question of interest. We also touch on the importance of general equilibrium effects and full cost–benefit analyses.     

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.     

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.     

何时联盟？何时并购？

联合与并购同样是战略选择,这意味着如果选择其中一种战略就得放弃另外一种。如果公司在决策中正确地应用战略选择,他们将会取得更好的业绩。     

Network architecture, cooperation and punishment in public good experiments

Following Fehr and G?echter (Am Econ Rev 90(4):980–994, 2000), a large and growing number of experiments show that public goods can be provided at high levels when mutual monitoring and costly punishment are allowed. Nearly all experiments, however, study monitoring and punishment in a complete network where all subjects can monitor and punish each other. The architecture of social networks becomes important when subjects can only monitor and punish the other subjects to whom they are connected by the network. We study several incomplete networks and find that they give rise to their own distinctive patterns of behavior. Nevertheless, a number of simple, yet fundamental, properties in graph theory allow us to interpret the variation in the patterns of behavior that arise in the laboratory and to explain the impact of network architecture on the efficiency and dynamics of the experimental outcomes.     

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.     

Understanding Error Structures and Exploiting Panel Data in Meta-analytic Benefit Transfers

A regression meta-analysis is a statistical summary of results from a set of empirical studies. While, a meta-analysis is typically used to drawn inferences regarding the collective insights from an empirical literature, a regression meta-analysis can also be used to predict outcomes as a substitute for the conduct of a new study. Within the nonmarket-valuation literature benefit transfers are a special case of prediction where value estimates collected for one purpose are used as a basis for predicting value for unstudied applications. Balancing against the prediction opportunities provided by a regression meta-analysis is the potential prediction error. This paper considers some of these issues in the estimation of a regression meta-analysis to support prediction of nonmarket values for applications where an original study does not exist. We do not purport to address all elements of the error structure and prediction issues, but to present a more coherent focus to enhance future research on the validity and reliability of benefit-function transfers, and ultimately assist in enhancing the credibility of benefit transfers to support policy analyses.     

Cost analysis of plasma-derived factor VIII/von Willebrand factor versus recombinant factor VIII for treatment of previously untreated patients with severe hemophilia A in the United States

Background: Inhibitor development to factor VIII (FVIII) hemophilia therapy results in increased complications and substantial economic costs. The SIPPET study, the first randomized controlled trial to compare the immunogenicity of plasma-derived FVIII (pdFVIII)/von Willebrand factor (VWF) and recombinant-DNA-derived FVIII (rFVIII), demonstrated higher inhibitor rates in previously untreated patients (PUPs) treated with rFVIII than in PUPs treated with pdFVIII/VWF.

Objective: To quantify the economic impact of treating PUPs with pdFVIII/VWF vs rFVIII.

Methods: An Excel-based clinical and economic model was developed from a US healthcare payer perspective and run over a 5-year period. The analysis utilized a cohort approach to model patient treatment and outcomes over a monthly cycle to quantify differences in costs of FVIII, bypassing agents, and hospitalizations for serious bleeds. Rates of high-titer inhibitor development were obtained from the SIPPET study. Patients developing high-titer inhibitors were treated with immune tolerance induction (ITI). Patients who developed low-titer inhibitors and those who did not develop inhibitors continued their usual FVIII treatment. Patients who were successfully treated with ITI returned to FVIII treatment, while unsuccessfully treated patients received bypassing agents. Total costs per treated patient were estimated and a one-way sensitivity analysis was conducted to quantify the impact of parameter uncertainty on the model outcomes.

Results: Total cumulative costs per patient over 5 years were $834,621 for pdFVIII/VWF patients and $1,237,163 for rFVIII patients, representing a total saving of $402,542 per patient over the 5-year period, for an average annual saving of $80,508 per patient.

Conclusions: Based on data from the SIPPET study, this analysis found that initiating FVIII treatment in severe hemophilia A PUPs with pdFVIII/VWF has the potential to offer substantial cost savings to healthcare payers, amounting to a one-third reduction in costs.     

A simple method for estimating unconditional heterogeneity distributions in correlated random effects models

I propose a general, simple approach to recovering an unconditional heterogeneity distribution when a conditional distribution has been estimated. The approach can be applied to cross section models and panel data models-both static and dynamic-with unobserved heterogeneity.