计量经济分析 = Econometric analysis

A review of the biological response to ionic dissolution products from bioactive glasses and glass-ceramics

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Economics of natural resources and the environment

This month, the Clinical Practice Guideline (CPG) column reviews the recently published guideline, Treating Tobacco Use and Dependence. This set of recommendations is available in a quick reference format and a more comprehensive clinician's guide that includes detailed information on the methodology and references used to develop the guidelines. Both are available in electronic and hard copy versions through a variety of sources, including the National Guidelines Clearinghouse, the Centers for Disease Control and Prevention, and the National Cancer Institute.

Treating tobacco use and dependence.

This article challenges Fixed Effects (FE) modelling as the ‘default’ for time-series-cross-sectional and panel data. Understanding different within- and between-effects is crucial when choosing modelling strategies. The downside of Random Effects (RE) modelling – correlated lower-level covariates and higher-level residuals – is omitted-variable bias, solvable with Mundlak’s (1978a) formulation. Consequently, RE can provide everything FE promises and more, as confirmed by Monte-Carlo simulations, which additionally show problems with Plumper and Troeger’s FE Vector Decomposition method when data are unbalanced. As well as incorporating time-invariant variables, RE models are readily extendable, with random coefficients, cross-level interactions, and complex variance functions. We argue not simply for technical solutions to endogeneity, but the substantive importance of context/heterogeneity, modelled using RE. The implications extend beyond political science, to all multilevel datasets. However, omitted variables could still bias estimated higher-level variable effects; as with any model, care is required in interpretation.

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Explaining Fixed Effects: Random Effects modelling of Time-Series Cross-Sectional and Panel Data

We investigate the relationship between productivity, size and age of large Australian firms employing more than 100 employees or holding assets in excess of $100 million. In addition, we also investigate the extent of productivity persistence among these firms by looking at transition matrices of productivity distribution and productivity-rank mobility. The empirical study is based on the IBISWorld database used to estimate translog cost function to measure (a residual based) productivity. We find evidence, though somewhat weak, that larger and older firms are on average less productive. Further, we find strong evidence for a high degree of inertia in terms of productivity ranking within an industry.

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Is Firm Productivity Related to Size and Age? The Case of Large Australian Firms

Objective

To evaluate the relationship between hospital volume and outcome by focusing on alternative measures of volume that capture specialization and overall throughput of hospitals.



Data Sources/Study Setting

Hospital administrative data from the state of Victoria, Australia; data contain 1,798,474 admitted episodes reported by 135 public and private acute-care hospitals.



Study Design

This study contrasts the volume–outcome relationship using regression models with different measures of volume; two-step and single-step risk-adjustment methods are used.



Data Collection/Extraction Methods

The sample is restricted to ischemic heart disease (IHD) patients (ICD-10 codes: I20–I25) admitted during 2001/02 to 2004/05.



Principal Findings

Overall hospital throughput and degree of specialization display more substantive implications for the volume–outcome relationship than conventional caseload volume measure. Two-step estimation when corrected for heteroscedasticity produces comparable results to single-step methods.



Conclusions

Different measures of volume could lead to vastly different conclusions about the volume–outcome relationship. Hospital specialization and throughput should both be included as measures of volume to capture the notion of size, focus, and possible congestion effects.

On the Hospital Volume and Outcome Relationship: Does Specialization Matter More Than Volume?

This paper considers the competitive effects of exclusive dealing contracts in a three-player game: an incumbent, an entrant who is more efficient but capacity constrained, and a buyer. The author shows that exclusive dealing contracts may represent an effective entry barrier--the incumbent is able to exclude the smaller entrant from the industry. The outcome is not socially efficient. The author then examines the ocean shipping market, where exclusive dealing contracts are a common practice and capacity consideration is important. He finds exclusive dealing contracts in liner shipping may have given linear conferences an unfair advantage. Copyright 1996 by Blackwell Publishing Ltd.

Excluding capacity-constrained entrants through exclusive dealing: theory and an application to ocean shipping

This paper investigates the effects of competition on hospital quality using hospital administration data from the State of Victoria, Australia. Hospital quality is measured by 30-day mortality rates and 30-day unplanned readmission rates. Competition is measured by Herfindahl-Hirschman index and the numbers of competing public and private hospitals. The paper finds that hospitals facing higher competition have lower unplanned admission rates. However, competition is related negatively to hospital quality when measured by mortality, albeit the effects are weak and barely statistically significant. The paper also finds that the positive effect of competition on quality as measured by unplanned readmission differs greatly depending on whether the hospital is publicly or privately owned.

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Effects of competition on hospital quality: an examination using hospital administrative data

This paper studies the link between competition and technical efficiency of public hospitals in the state of Victoria, Australia. It finds a positive relationship between efficiency and competition as measured by the Hirschman-Herfindahl Index (HHI) and a negative relationship when the number of competing private hospitals is used instead of HHI. It also finds that whether or not quality is treated as an endogenous output variable influences the statistical estimates of the link between efficiency and competition. The findings point to possibly undesirable resource allocation effects when public hospitals are made to compete with a large number of private hospitals.

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Jongsay Yong

Papers

Is Firm Productivity Related to Size and Age? The Case of Large Australian Firms

On the Hospital Volume and Outcome Relationship: Does Specialization Matter More Than Volume?

Excluding capacity-constrained entrants through exclusive dealing: theory and an application to ocean shipping

Effects of competition on hospital quality: an examination using hospital administrative data

Hospital Competition, Technical Efficiency and Quality