The Econometric Analysis of Constructed Binary Time Series. Working paper #1

Macroeconometric and financial researchers often use secondary or constructed binary random variables that differ in terms of their statistical properties from the primary random variables used in microeconometric studies. One important difference between primary and secondary binary variables is that while the former are, in many instances, independently distributed (i.d.) the later are rarely i.d. We show how popular rules for constructing binary states determine the degree and nature of the dependence in those states. When using constructed binary variables as regressands a common mistake is to ignore the dependence by using a probit model. We present an alternative non-parametric method that allows for dependence and apply that method to the issue of using the yield spread to predict recessions.Business cycle; binary variable, Markov chain, probit model, yield curve

Retail Pricing Behavior for Perishable Produce Products in the US with Implications for Farmer Welfare

The typical model of retail pricing for produce products assumes retailers set price equal to the farm price plus a certain markup. However, observations from scanner data indicate a large degree of price dispersion in the grocery retailing market. In addition to markup pricing behavior, we document three alternative leading pricing patterns: fixed (constant) pricing, periodic sale, and high-low pricing. Retail price variations under these alternative pricing regimes in general have little correlation with the farm price. How do retailers’ alternative pricing behaviors affect farmers’ welfare? Using markup pricing as the baseline case, we parameterize the model to reflect a prototypical fresh produce market and carry out a series of simulations under different pricing regimes. Our study shows that if harvest cost is sufficiently low, retail prices adjusting only partially, or not at all, to supply shocks tends to diminish farm income and exacerbate farm price volatility relative to the baseline case. However, we also find that if harvest cost is sufficiently large and the harvest-cost constraint places a lower bound on the farm price, increased farm price volatility induced by retailers’ alternative pricing strategies may result in higher farm income, compared to markup pricing. Our study is the first to evaluate the welfare implications for producers of the diversified pricing strategies that retailers utilize in practice and the resulting attenuation of the relationship between prices at retail and at the farm gate.Agribusiness, Demand and Price Analysis,

Towards Automatic Face-to-Face Translation

In light of the recent breakthroughs in automatic machine translation systems, we propose a novel approach that we term as "Face-to-Face Translation". As today's digital communication becomes increasingly visual, we argue that there is a need for systems that can automatically translate a video of a person speaking in language A into a target language B with realistic lip synchronization. In this work, we create an automatic pipeline for this problem and demonstrate its impact on multiple real-world applications. First, we build a working speech-to-speech translation system by bringing together multiple existing modules from speech and language. We then move towards "Face-to-Face Translation" by incorporating a novel visual module, LipGAN for generating realistic talking faces from the translated audio. Quantitative evaluation of LipGAN on the standard LRW test set shows that it significantly outperforms existing approaches across all standard metrics. We also subject our Face-to-Face Translation pipeline, to multiple human evaluations and show that it can significantly improve the overall user experience for consuming and interacting with multimodal content across languages. Code, models and demo video are made publicly available. Demo video: https://www.youtube.com/watch?v=aHG6Oei8jF0 Code and models: https://github.com/Rudrabha/LipGANComment: 9 pages (including references), 5 figures, Published in ACM Multimedia, 201

Efficient, collision-free multi-robot navigation in an environment abstraction framework

Industrial automation deploys a continuously increasing amount of mobile robots in favor of classical linear conveyor systems for material flow handling in manufacturing and intralogistics. This increases flexibility by handling a larger variety of goods, improves scalability by adapting the fleet size to varying system loads, and enhances fault tolerance by avoiding single points of failure. However, it also raises the need for efficient, collision-free multi-robot navigation. This core problem is first precisely modeled in a form that differs from existing approaches specifically in terms of application relevance and structured algorithmic treatability. Collision-free trajectories for the mobile robots between given start and goal locations are sought so that the number of goals reached per time is as high as possible. Based on this, a decoupled solution called the Collaborative Local Planning Framework (CLPF), is designed and implemented, which, in contrast to existing solutions, aims at avoiding deadlocks with the greatest possible concurrency. Moreover, this solution includes the handling of dynamic inputs consisting of both moving and non-moving robots. For testing, performance analysis, and optimization, due to the complexity of multi-robot systems, the use of simulation is common. However, this also creates a gap between real and simulated robots. These issues can be reduced by using several different simulators---albeit with the disadvantage of further increasing complexity. For this purpose, the Robot Experimentation Framework (REF) is introduced to write robotic experiments with a unified interface that can be run on multiple simulators and also on real hardware. It facilitates the creation of experiments for performance assessment, (parameter) optimization and runtime analysis. The framework has proven its effectiveness throughout this thesis. Lastly, experimental proof of the viability of the solution is provided based on a case study of a complete (simulated) assembly system of decentralized autonomous agents for the production of highly individualized automobiles. This integrates all developed concepts into a holistic application of industrial automation. Detailed evaluations of more than 800 000 solved scenarios with more than 5 700 000 processed goals have experimentally proven the robustness and reliability of the developed concepts. Robots have never crashed into each other in any of the conducted experiments, empirically proving the claimed safety guarantees. A fault-tolerance analysis of the decentralized assembly system has experimentally proven its resilience to failures at workstations and, thus, specifically revealed an advantage over linear conveyor systems