PRICE MATCHING AND THE DOMINO EFFECT IN A RETAIL GASOLINE MARKET

Using gasoline station price data collected eight times per day for 103 d for 27 stations in Guelph, Ontario, it is found that, consistent with an informal theory of competitive gasoline pricing, stations set prices to match a small number of other stations. However, these matched stations are not necessarily the closest. While retailers frequently respond to price changes within 2 h, many take considerably longer. Finally, while price decreases do ripple across the market like falling dominos, increases propagate across the city based more on geographic location and source of price control than on proximity to leaders of these increases. ( JEL L13, L40, L81)     

Changes in Americans' Policy Preferences, 1935-1979

Using responses to 3,315 survey questions asked of nationalsamples, we examine how policy preferences of Americans havechanged over the last 45 years. The data indicate that therehas been considerable stability in public opinion: responsesto half the 613 repeated policy items show no significant changeat all; approximately half the detectable changes were lessthan 10 percentage points; and rarely did preferences fluctuatesignificantly back and forth within a short time period. Foreignpolicy changes were no larger or more frequent than domestic,but they did tend to occur more abruptly. When opinion shiftsoccurred, they were not random or capricious; they were usuallyrelated to important changes in citizens' social and economicenvironments. Rapid shifts generally coincided with major eventsin international affairs or the economy.     

Parameter Estimation for a Bidimensional Partially Observed Ornstein–Uhlenbeck Process with Biological Application

Abstract. We consider a bidimensional Ornstein–Uhlenbeck process to describe the tissue microvascularization in anti‐cancer therapy. Data are discrete, partial and noisy observations of this stochastic differential equation (SDE). Our aim is to estimate the SDE parameters. We use the main advantage of a one‐dimensional observation to obtain an easy way to compute the exact likelihood using the Kalman filter recursion, which allows to implement an easy numerical maximization of the likelihood. Furthermore, we establish the link between the observations and an ARMA process and we deduce the asymptotic properties of the maximum likelihood estimator. We show that this ARMA property can be generalized to a higher dimensional underlying Ornstein–Uhlenbeck diffusion. We compare this estimator with the one obtained by the well‐known expectation maximization algorithm on simulated data. Our estimation methods can be directly applied to other biological contexts such as drug pharmacokinetics or hormone secretions.     

STICKY PRICE AND STICKY INFORMATION PRICE‐SETTING MODELS: WHAT IS THE DIFFERENCE?

Using a partial equilibrium framework, Mankiw and Reis show that a sticky information model can generate a lagged and gradual inflation response after a monetary policy shock, whereas a sticky price model cannot. Our study demonstrates that the finding is sensitive to their model's parameterization. To determine a plausible parameterization, we specify a general equilibrium model with sticky information. In that model, we find that inflation peaks only one period after a monetary disturbance. A sensitivity analysis of our results reveals that the inflation peak is delayed by including real rigidities when the monetary policy instrument is money growth, whereas inflation peaks immediately when the policy instrument is the nominal interest rate. ( JEL E31, E32, E52)