Mixed Logit Estimation of the Value of Travel Time

In this paper we use mixed logit specifications to allow parameters to vary in the population when estimating the value of time for long-distance car travel. Our main conclusion is that the estimated value of time is very sensitive to how the model is specified: we find that it is significantly lower when the coefficients are assumed to be normally distributed in the population, as compared to the traditional case when they are treated as fixed. In our most richly parameterised model, we find a median value of time of 57 SEK per hour, with the major part of the mass of the value of time distribution closely centred around the median value. The corresponding figure when the parameters are treated as fixed is 89 SEK per hour. Furthermore, our finding that the ratio of coefficients in a mixed logit specification differ significantly from the ones in a traditional logit specification is contrary to the results obtained by Brownstone & Train (1996) and Train (1997). Whether the ratios will differ or not depends on the model and the data generating process at hand.Mixed Logit; Simulation Estimation; Value of Time

The national Swedish value of time study

In Sweden, cost benefit evaluations have been part of the planning process for many years. In these cost benefit evaluations, the value of time plays an important role. This project aims at providing VoT’s for new guidelines for project evaluation. A more general aim of the study is to provide more insight in VoT issues, especially for business trips. The Hensher formula was used for calculation of the VoT’s for business trips. But as the aim was to look deeper into business trips, it was decided to extract samples also for behaviour values and for the group of self-employed persons. The project was carried out in Sweden 1994/95. It is concentrated to regional and long distance trips, since they will be the most important trip types in the evaluation work. Approximately 5000 interviews were completed

Feature-Aware Point Transformer for Point Cloud Alignment Classification : Pose your pose to FACT

As the demand for 3D maps from LIDAR scanners increases, delivering high-quality maps becomes critical. One way to ensure the quality of such maps is through point cloud alignment classification, which aims to classify the alignment error between two registered point clouds. Specifically, we present the classifier FACT (Feature-Aware Classification Transformer), consisting of two main modules: feature extraction and classification. Descriptive features are extracted from the joint point cloud, which are then processed by a point transformer-based neural network to predict the alignment error class. In a ten-class point cloud alignment classification test, FACT achieved 92.4% accuracy, where the alignment error ranged from zero meters and radians to 0.9 meters and 0.09 radians. Remarkably, the classifier only made one misprediction beyond neighboring classes, exhibiting its ability to detect alignment errors as the classes have an inherent order. Furthermore, when benchmarked on two binary classification tasks, FACT showed significantly superior performance over the baseline and even obtained 100.0% accuracy for the easier of the two tasks. FACT not only detects potential errors in 3D maps but also estimates their magnitude, leading to more reliable 3D maps with quality estimations for each transformation

Feature-Aware Point Transformer for Point Cloud Alignment Classification : Pose your pose to FACT

As the demand for 3D maps from LIDAR scanners increases, delivering high-quality maps becomes critical. One way to ensure the quality of such maps is through point cloud alignment classification, which aims to classify the alignment error between two registered point clouds. Specifically, we present the classifier FACT (Feature-Aware Classification Transformer), consisting of two main modules: feature extraction and classification. Descriptive features are extracted from the joint point cloud, which are then processed by a point transformer-based neural network to predict the alignment error class. In a ten-class point cloud alignment classification test, FACT achieved 92.4% accuracy, where the alignment error ranged from zero meters and radians to 0.9 meters and 0.09 radians. Remarkably, the classifier only made one misprediction beyond neighboring classes, exhibiting its ability to detect alignment errors as the classes have an inherent order. Furthermore, when benchmarked on two binary classification tasks, FACT showed significantly superior performance over the baseline and even obtained 100.0% accuracy for the easier of the two tasks. FACT not only detects potential errors in 3D maps but also estimates their magnitude, leading to more reliable 3D maps with quality estimations for each transformation

Contingent claims valuation when the payoff depends on the price level: An index-linked bond approach

This paper analyses how to price contingent claims, the payoffs which depend on the price level, by using an index-linked bond as the underlying asset. The analysis takes place in an economy where the nominal instantaneous rate of interest (the spot rate) is stochastic. A closed formula for options is presented as well as an investigation of how sensitive this formula is to variations in the parameters of the formula. It turns out that the volatility of the index-linked bond price heavily affects the option price and that the correlation between the spot rate and the return of the index-linked bond is of potential importance. Different areas of application, such as loan contracts in the housing sector and inflation insurances in pension plans, are also discussed.Inflation risk option pricing stochastic interest rate volatility loan contracts inflation insurance

Inflation Targeting and the Dynamics of the Transmission Mechanism

This paper derives closed-form expressions for optimal monetary policy rules when the central bank can influence inflation directly with a one-period lag as well as a two-period lagged effect via the output gap. It turns out that even a modest one-period inflation effect from monetary policy actions has substantial implications for monetary policy that also seem to be a step towards increased realism. For instance, in models where the central bank only can affect inflation with a two-period lag via the output gap, policy becomes more aggressive and the output gap exhibits a tendency to switch sign frequently. This unrealistic oscillating feature can be avoided by allowing the central bank to influence inflation with a one-period lag. The model also illustrates that the nature of empirical (or reduced-form) Phillips curves may reflect monetary policy and the observation that the Phillips curve in recent years has become flatter can in this model be explained by a more counter-cyclical monetary policy.Inflation targeting; optimal monetary policy; the transmission mechanism

The Monetary Policy Decision-Making Process and the Term Structure of Interest Rates

This paper presents a theoretical model of the term structure of interest rates based on the monetary policy decision-making process at modern central banks. Evaluations of explicit expressions for the spot and forward rate curve render several important results: (i) Spot and forward rates are explicit functions of the number of policy meetings during the time to maturity rather than the time to maturity itself. Consequently, the forward rate curve is step-shaped. (ii) In addition, there are calendar time effects, i.e. the position within the policy cycle is also of importance, especially for short term interest rates. (iii) The forward rate curve exhibits hump-shaped responses to economic shocks and a modified version of the Nelson-Siegel model can be obtained as a special case.The term structure of interest rates; interest rate stepping; policy gap; calendar time effects; hump-shaped responses

Macroeconomic Externalities : Are Pigovian Taxes the Answer?

Basic welfare economics tells us that many types of externalities can be remedied by proper use of corrective taxes and subsidies. This paper shows that this notion also extends to the macroeconomic externalities discussed in recent Keynesian literature on nominal price rigidities. The derived policy rules are lindred in spirit to standard Keynesian policy prescriptions: Progressive income taxes may serve a useful role in combating wasteful economic fluctuations. However, unlike older fix-price models of automatic stabilizers, progressive taxes work in our monopolistic economy because they directly affect the pricing mechanism

Mixed Logit Estimation of the Value of Travel Time

In this paper we use mixed logit specifications to allow parameters to vary in the population when estimating the value of time for long-distance car travel. Our main conclusion is that the estimated value of time is very sensitive to how the model is specified: we find that it is significantly lower when the coefficients are assumed to be normally distributed in the population, as compared to the traditional case when they are treated as fixed. In our most richly parameterised model, we find a median value of time of 57 SEK per hour, with the major part of the mass of the value of time distribution closely centred around the median value. The corresponding figure when the parameters are treated as fixed is 89 SEK per hour. Furthermore, our finding that the ratio of coefficients in a mixed logit specification differ significantly from the ones in a traditional logit specification is contrary to the results obtained by Brownstone & Train (1996) and Train (1997). Whether the ratios will differ or not depends on the model and the data generating process at hand