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A major source of external funding for US airports comes from issuing municipal bonds. Credit rating agencies evaluate the bonds using multiple factors, but the judgments behind the ratings are not well understood. This paper examines if airport rate-setting methods affect the bond ratings of US airports.

Using a set of unbalanced panel data for 58 hub airports from 2010 to 2019, we examine the effect of the rate-setting methods and other airport characteristics on Fitch’s airport bond rating.

We find that compensatory airports consistently receive a very high bond rating from Fitch. The probability of getting a very high Fitch rating increases by ∼28 percentage points for a compensatory airport. Additionally, the probability of getting a very high rating is about 33 percentage points higher for a legacy hub.

The study uses Fitch bond ratings. Future studies could examine if S&P’s and Moody’s ratings are also influenced by airport rate-setting methods and legacy hub status.

The results uncover the linkage between bond ratings and their determinants for US airports. This information is important for investors when assessing airport creditworthiness and for airport operators as they manage capital project financing.

This is the first study to evaluate the effects of rate-setting methods on airport bond rating and also the first to document a statistically significant relationship between airports’ legacy hub status and bond ratings.

Traditionally, economic production models consider pollution as bads that may be modeled as either outputs or inputs in economic models. The purpose of this paper is to examine the implications of these modeling choices on the measurements of productive efficiency and private costs of pollution control.

The authors apply the hyperbolic distance functions to measure trucking efficiency and the private costs of pollution control.

The results show: (i) regardless of the choice of modeling, when only one bad was incorporated in hyperbolic distance functions, the efficiency loss and private abatement cost measures derived from the two models were equivalent, but potential pollution reduction and good output expansion differed; (ii) when more than one bad were introduced, the equivalence of efficiency loss measure in (i) did not hold; and (iii) the potential amounts of pollution reduction and good output expansion were larger when bads were modeled as inputs. With multiple bads, private abatement costs varied considerably under the two modeling treatments.

From a policy standpoint, the results suggest that one should consider the modeling options with caution when multiple economic bads are involved, because the resulting measures of economic burden of pollution control differ.

The paper shows that the traditional conceptual framework for modeling pollution in hyperbolic distance functions could yield inconsistent results.

The purpose of this paper is to provide an economic assessment of the productivity growth and technical efficiency of US Class I railroads for the period of 2002‐2007.

The US railroad industry has become increasingly concentrated with seven Class I railroads accounting for over 90 percent of the industry's revenue. Because the small sample size creates a dimensionality problem for data envelopment analysis (DEA) with contemporaneous frontiers, the authors use sequential DEA and calculate the Malmquist productivity indexes using sequential frontiers. Through a decomposition process, changes in productivity are attributed to technical efficiency change, technical change, and scale efficiency change.

Burlington Northern Santa Fe (BNSF) led the industry in terms of productivity growth (4.6 percent) and consistently stayed on the production frontier in every period studied; both BNSF and Union Pacific (UP) are top innovators in the industry, but UP trailed BNSF in both productivity growth and technological innovations by wide margins; and Grand Trunk Corporation was very good at “catching up” or leading its peers in efficiency improvements.

Railroads have invested heavily in technology over the years to enhance efficiency and productivity. However, two recent economic studies find that railroad productivity has slowed in recent years. The authors' benchmarking analysis sheds light on how individual railroads performed relative to their peers, and what they could learn from industry best practice.

The benchmarking study enables the authors to report each railroad's performance instead of reporting industry‐wide aggregate indexes or industry averages which tend to mask performance variations. The paper also examines the causal factors of recent productivity growth and provides useful information for the industry and its regulators.

Respondents from five Asian countries were surveyed in terms of their consumer ethnocentrism, animosity, and attribution towards the USA and Japan in the context of the Asian economic crisis. The results indicated that the more severely hit a country was, the more ethnocentric respondents were. In general, animosity towards the USA was higher than towards Japan with regard to the Asian crisis. Koreans held the greatest stable animosity towards the Japanese because of the atrocities experienced during the Second World War. Respondents attributed the blame of the Asian crisis more to themselves. They also felt that they and the Japanese could have controlled the turn of events during the crisis. Implications arising from the findings are discussed.