International Benchmarking for Monopoly Price Regulation: The Case of Australian Gas Distribution

Price-cap regulation is widely applied to network industries. However, regulators often encounter the problem of asymmetric information on efficient costs. Benchmarking can help reduce this problem. We present a benchmarking analysis, conducted for an Australian regulator, that derives measures of efficiency for Australian gas distributors relative to U.S. counterparts. Several techniques, such as data envelopment analysis and stochastic frontier analysis, are used to ensure that our measures are robust to methodology choice. We conclude with a discussion of how the regulator used the benchmarking results, along with other information, to help it determine appropriate price caps.     

Precautionary Demand for Education, Inequality, and Technological Progress

This paper offers an explanation for the evolution of wage inequality within and between industries and education groups over the past several decades. The model is based on the disproportionate depreciation of technology-specific skills versus general skills due to technological progress, which occurs randomly across sectors. Consistent with empirical evidence, the model predicts that increasing randomness is the primary source of inequality growth within uneducated workers, whereas inequality growth within educated workers is determined more by changes in the composition and return to ability. Increasing randomness generates a precautionary demand for education, which we show empirically to be significant.     

Estimating aggregate autoregressive processes when only macro data are available

The aggregation of individual random AR(1) models generally leads to an AR(∞$\infty$) process. We provide two consistent estimators of aggregate dynamics based on either a parametric regression or a minimum distance approach for use when only macro data are available. Notably, both estimators allow us to recover some moments of the cross-sectional distribution of the autoregressive parameter. Both estimators perform very well in our Monte-Carlo experiment, even with finite samples.     

A passenger demand model for air transportation in a hub-and-spoke network

This paper develops an air passenger model that deals with city-pair demand generation and demand assignment in a single framework. Using publicly available and regularly collected panel data, the model captures both time series and cross-sectional variation of air travel demand. The empirical analysis finds that pattern of correlations among alternatives can be described by a three-level nested logit model. Fare, frequency, flight time, direct routing, on-time performance, income, and market distance have significantly effects on air demand. Correcting for the problem of endogenous air fares using instrumental variables yields more plausible estimates of price sensitivity and value of time.