Simulation of Land Use and Investment Behaviour under Different Policy Scenarios: Results of the extended farm/household model. Factor Markets Working Paper No. 27, July 2012

Factor markets are a central issue in analyses of farm development and of agricultural sector vitality. Among the different production factors, land is one of the most studied. Several studies seek to estimate the effect of government policy payments on land value or land rental prices. The studies mostly agree that government payments and other types of policy support are significant in explaining land prices and account for a large share of them. In October 2011, the European Commission published a new policy proposal for the common agricultural policy (CAP) up to 2020. The proposed regulation includes a shift from historical to regional payments. The objective of this paper is to provide an ex ante analysis of the impact of the new CAP policy instruments on the land market. In particular, the effect of the regionalisation of payments in Italy is examined. The analysis is based on the use of a mathematical programming model to simulate the changes in land demand for a farm in Emilia Romagna. The results highlight the relevance of the new policy mechanism in determining a change in land demand. Yet the effect is highly dependent on initial ownership of entitlements under the historical payment scheme.

The Danish Flexicurity Model - a Lesson for the US? ACES Working Paper No. 2, May 2007

Within recent years, increasing international competition has caused an increase in job transitions worldwide. Many countries find it difficult to manage these transitions in a way that ensures a match between labour and demand. One of the countries that seem to manage the transitions in a successful way is Denmark, where unemployment has been dropping dramatically over the last decade without a drop in job quality. This success is ascribed the so-called Danish flexicurity model, where an easy access to hiring and firing employees (flexibility) is combined with extensive active and passive labour market policies (security). The Danish results have gained interest not only among other European countries, where unemployment rates remain high, but also in the US, where job loss is often related to lower job quality. It has, however, been subject to much debate both in Europe and in the US, whether or not countries with distinctively different political-economic settings can learn from one another. Some have argued that cultural differences impose barriers to successful policy transfer, whereas others see it as a perfectly rational calculus to introduce 'best practices' from elsewhere. This paper presents a third strategy. Recent literature on policy transfer suggests that successful cross national policy transfer is possible, even across the Atlantic, but that one must be cautious in choosing the form, content and level of the learning process. By analysing and comparing the labour market policies and their settings in Denmark and the US in detail, this paper addresses the question, what and how the US can learn from the Danish model. Where the US and Denmark share a high degree of flexibility, they differ significantly on the level of security. This also means that the Danish budget for active and passive labour market policies is significantly higher than the American, and it seems unlikely that political support for the introduction of Danish levels of security in the US can be established. However, the paper concludes that there is a learning potential between the US and Demnark in the different local level efficiency of the money already spent. A major reason for the Danish success has been the introduction of tailor made initiatives to the single displaced worker and a stronger coordination between local level actors. Both of which are issues, where a lack of efficiency in the implementation of American active labour market policies has been reported.

Prospects for Energy Supply and Demand in the Southern Mediterranean: Scenarios for 2010-30. MEDPRO Technical Report No. 22/December 2012

The aim of this technical report is to quantify alternative energy demand and supply scenarios for ten southern and eastern Mediterranean countries up to 2030. The report presents the model-based results of four alternative scenarios that are broadly in line with the MEDPRO scenario specifications on regional integration and cooperation with the EU. The report analyses the main implications of the scenarios in the following areas: • final energy demand by sector (industry, households, services, agriculture and transport); • the evolution of the power generation mix, the development of renewable energy sources and electricity exports to the EU; • primary energy production and the balance of trade for hydrocarbons; • energy-related CO2 emissions; and • power generation costs.

Modeling and validation of the thermal behavior of buildings for the development of demand response methods

The representation of the thermal behaviour of the building is achieved through a relatively simple dynamic model that takes into account the effects due to the thermal mass of the building components. The model of a intra-floor apartment has been built in the Matlab-Simulink environment and considers the heat transmission through the external envelope, wall and windows, the internal thermal masses, (i.e. furniture, internal wall and floor slabs) and the sun gain due to opaque and see-through surfaces of the external envelope. The simulations results for the entire year have been compared and the model validated, with the one obtained with the dynamic building simulation software Energyplus.

Additional traffic assignment options for the TASSIM model. Phase I. Final report.

Transportation Department, Washington, D.C.

The Department of Transportation long-range forecast model. Final report.

Transportation Department, Office of Intermodal Transportation, Washington, D.C.

Rail-highway crossing resource allocation model. Final report.

Federal Railway Administration, Office of Safety, Washington, D.C.

Consumer behavior towards fuel efficient vehicles. Volume IV: operating instructions and programs documentation for the CS Vehicle Choice Simulation Model. Final report.

National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.

The value of travel time: new estimates developed using a speed-choice model. Final report.

Mode of access: Internet.

Highway fuel consumption computer model (version I). Final report.

Transportation Department, Washington, D.C.

Forecasting auto ownership and mode choice for U.S. metropolitan areas. Volume II: model equations. Final report.

Transportation Department, Office of University Research, Washington, D.C.

Nonparametric Identication and Structural Estimation of Auction Models

Thesis (Ph.D.)--University of Washington, 2016-06

Discovering user access pattern based on probabilistic latent factor model

There has been an increased demand for characterizing user access patterns using web mining techniques since the informative knowledge extracted from web server log files can not only offer benefits for web site structure improvement but also for better understanding of user navigational behavior. In this paper, we present a web usage mining method, which utilize web user usage and page linkage information to capture user access pattern based on Probabilistic Latent Semantic Analysis (PLSA) model. A specific probabilistic model analysis algorithm, EM algorithm, is applied to the integrated usage data to infer the latent semantic factors as well as generate user session clusters for revealing user access patterns. Experiments have been conducted on real world data set to validate the effectiveness of the proposed approach. The results have shown that the presented method is capable of characterizing the latent semantic factors and generating user profile in terms of weighted page vectors, which may reflect the common access interest exhibited by users among same session cluster.

Promoting creativity at work:the role of problem-solving demand

We propose that problem-solving demand (PSD) is an important job attribute for employees' creative performance. Applying job design theory, we examined the relationship between PSD and employee creativity. The theorised model was tested with data obtained from a sample of 270 employees and their supervisors from three Chinese organisations. Regression results revealed that PSD was positively related to creativity, and this relationship was mediated by creative self-efficacy. Additionally, intrinsic motivation moderated the relationship between PSD and creative self-efficacy such that the relationship was stronger for individuals with high rather than low intrinsic motivation. We discuss our findings, implications for practice, and future research.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.