What works best for getting the unemployed back to work: employment services or small-business assistance programs? evidence from Romania

Recent empirical evidence has found that employment services and small-business assistance programmes are often successful at getting the unemployed back to work. Â One important concern of policy makers is to decide which of these two programmes is more effective and for whom. Â Using unusually rich (for transition economies) survey data and matching methods, I evaluate the relative effectiveness of these two programmes in Romania. Â While I find that employment services (ES) are, on average, more successful than a small-business assistance programme (SBA), estimation of heterogeneity effects reveals that, compared to non-participation, ES are effective for workers with little access to informal search channels, and SBA works for less-qualified workers and those living in rural areas. Â When comparing ES to SBA, I find that ES tend to be more efficient than SBA for workers without a high-school degree, and that the opposite holds for the more educated workers.

Compliment de les directrius DRIVER dels repositoris cooperatius RACO, RECERCAT i TDX

Aquest informe ha estat elaborat per encàrrec del Consorci de Biblioteques Universitàries de Catalunya (CBUC). El seu objectiu és comprovar si des del punt de vista tècnic, els repositoris cooperatius que el CBUC coordina juntament amb el Centre de Supercomputació de Catalunya (CESCA), es poden integrar dins la infrastructura DRIVER.

A new approach to real time traffic sign recognition based on colour information

The automatic interpretation of conventional traffic signs is very complex and time consuming. The paper concerns an automatic warning system for driving assistance. It does not interpret the standard traffic signs on the roadside; the proposal is to incorporate into the existing signs another type of traffic sign whose information will be more easily interpreted by a processor. The type of information to be added is profuse and therefore the most important object is the robustness of the system. The basic proposal of this new philosophy is that the co-pilot system for automatic warning and driving assistance can interpret with greater ease the information contained in the new sign, whilst the human driver only has to interpret the "classic" sign. One of the codings that has been tested with good results and which seems to us easy to implement is that which has a rectangular shape and 4 vertical bars of different colours. The size of these signs is equivalent to the size of the conventional signs (approximately 0.4 m2). The colour information from the sign can be easily interpreted by the proposed processor and the interpretation is much easier and quicker than the information shown by the pictographs of the classic signs

Driver scheduling problem modelling

The Drivers Scheduling Problem (DSP) consists of selecting a set of duties for vehicle drivers, for example buses, trains, plane or boat drivers or pilots, for the transportation of passengers or goods. This is a complex problem because it involves several constraints related to labour and company rules and can also present different evaluation criteria and objectives. Being able to develop an adequate model for this problem that can represent the real problem as close as possible is an important research area.The main objective of this research work is to present new mathematical models to the DSP problem that represent all the complexity of the drivers scheduling problem, and also demonstrate that the solutions of these models can be easily implemented in real situations. This issue has been recognized by several authors and as important problem in Public Transportation. The most well-known and general formulation for the DSP is a Set Partition/Set Covering Model (SPP/SCP). However, to a large extend these models simplify some of the specific business aspects and issues of real problems. This makes it difficult to use these models as automatic planning systems because the schedules obtained must be modified manually to be implemented in real situations. Based on extensive passenger transportation experience in bus companies in Portugal, we propose new alternative models to formulate the DSP problem. These models are also based on Set Partitioning/Covering Models; however, they take into account the bus operator issues and the perspective opinions and environment of the user.We follow the steps of the Operations Research Methodology which consist of: Identify the Problem; Understand the System; Formulate a Mathematical Model; Verify the Model; Select the Best Alternative; Present the Results of theAnalysis and Implement and Evaluate. All the processes are done with close participation and involvement of the final users from different transportation companies. The planner s opinion and main criticisms are used to improve the proposed model in a continuous enrichment process. The final objective is to have a model that can be incorporated into an information system to be used as an automatic tool to produce driver schedules. Therefore, the criteria for evaluating the models is the capacity to generate real and useful schedules that can be implemented without many manual adjustments or modifications. We have considered the following as measures of the quality of the model: simplicity, solution quality and applicability. We tested the alternative models with a set of real data obtained from several different transportation companies and analyzed the optimal schedules obtained with respect to the applicability of the solution to the real situation. To do this, the schedules were analyzed by the planners to determine their quality and applicability. The main result of this work is the proposition of new mathematical models for the DSP that better represent the realities of the passenger transportation operators and lead to better schedules that can be implemented directly in real situations.

Metaheuristics for the bus-driver scheduling problem

We present new metaheuristics for solving real crew scheduling problemsin a public transportation bus company. Since the crews of thesecompanies are drivers, we will designate the problem by the bus-driverscheduling problem. Crew scheduling problems are well known and severalmathematical programming based techniques have been proposed to solvethem, in particular using the set-covering formulation. However, inpractice, there exists the need for improvement in terms of computationalefficiency and capacity of solving large-scale instances. Moreover, thereal bus-driver scheduling problems that we consider can present variantaspects of the set covering, as for example a different objectivefunction, implying that alternative solutions methods have to bedeveloped. We propose metaheuristics based on the following approaches:GRASP (greedy randomized adaptive search procedure), tabu search andgenetic algorithms. These metaheuristics also present some innovationfeatures based on and genetic algorithms. These metaheuristics alsopresent some innovation features based on the structure of the crewscheduling problem, that guide the search efficiently and able them tofind good solutions. Some of these new features can also be applied inthe development of heuristics to other combinatorial optimizationproblems. A summary of computational results with real-data problems ispresented.

Driver costs in small firms: Empirical analysis for farms

The agricultural sector has always been characterized by a predominance of small firms. International competition and the consequent need for restraining costs are permanent challenges for farms. This paper performs an empirical investigation of cost behavior in agriculture using panel data analysis. Our results show that transactions caused by complexity influence farm costs with opposite effects for specific and indirect costs. While transactions allow economies of scale in specific costs, they significantly increase indirect costs. However, the main driver for farm costs is volume. In addition, important differences exist for small and big farms, since transactional variables significantly influence the former but not the latter. While sophisticated management tools, such ABC, could provide only limited complementary useful information but no essential allocation bases for farms, they seem inappropriate for small farms

Driver costs in small firms: Empirical analysis for farms

The agricultural sector has always been characterized by a predominance of small firms. International competition and the consequent need for restraining costs are permanent challenges for farms. This paper performs an empirical investigation of cost behavior in agriculture using panel data analysis. Our results show that transactions caused by complexity influence farm costs with opposite effects for specific and indirect costs. While transactions allow economies of scale in specific costs, they significantly increase indirect costs. However, the main driver for farm costs is volume. In addition, important differences exist for small and big farms, since transactional variables significantly influence the former but not the latter. While sophisticated management tools, such ABC, could provide only limited complementary useful information but no essential allocation bases for farms, they seem inappropriate for small farms