Trade Intensity and Business Cycle Synchronization: Are Developing Countries any Different?

Some key criteria in the optimal currency area literature are that countries should join a currency union if they have closer international trade links and more symmetric business cycles. However, both criteria are endogenous. Frankel and Rose (1998) find that trade intensity increases cycle correlation among industrial countries. We study whether the same result holds true for the case of developing countries, as their different patterns of international trade and specialization may lead to cyclical asymmetries among them and between industrial and developing countries. We gather annual information for 147 countries for 1960-99 (33,676 country pairs) and find: (i) countries with higher bilateral trade exhibit higher business cycle synchronization, with an increase of one standard deviation in bilateral trade intensity raising the output correlation from 0. 05 to 0. 09 for all country pairs; (ii) countries with more asymmetric structures of production exhibit a smaller business cycle correlation; (iii) the impact of trade integration on business cycles is higher for industrial countries than both developing and industrial-developing country pairs; (iv) a one standard deviation increase in bilateral trade intensity leads to surges in output correlation from 0. 25 to 0. 39 among industrial countries, from 0. 08 to 0. 10 for our sample of industrial-developing country pairs, and from 0. 03 to 0. 06 among developing countries; (v) the impact of trade intensity on cycle correlation is smaller the greater the production structure asymmetries between the countries.

Can the standard international business cycle model explain the relation between trade and comovement?

Recent empirical research finds that pairs of countries with stronger trade linkages tend to have more highly correlated business cycles. We assess whether the standard international business cycle framework can replicate this intuitive result. We employ a three-country model with transportation costs. We simulate the effects of increased goods market integration under two asset market structures: complete markets and international financial autarky. Our main finding is that under both asset market structures the model can generate stronger correlations for pairs of countries that trade more, but the increased correlation falls far short of the empirical findings. Even when we control for the fact that most country pairs are small with respect to the rest of the world, the model continues to fall short. We also conduct additional simulations that allow for increased trade with the third country or increased TFP shock comovement to affect the country pair’s business cycle comovement. These simulations are helpful in highlighting channels that could narrow the gap between the empirical findings and the predictions of the model.Business cycles ; International trade

Business cycle synchronisation: disentangling trade and financial linkages

Drawing on a large sample of countries, this paper explores whether closer economic ties between countries foster business cycle synchronisation and disentangles the role of the various channels, including trade and financial linkages as well as the similarity in sectoral specialisation. Overall, our results confirm that trade integration fosters business cycle synchronisation. Similar patterns of sectoral specialisation also lead to closer business cycle co-movement. By contrast, it remains difficult to find a direct relationship between bilateral financial linkages and output correlation. However, our results suggest that financial integration affects business cycle synchronisation indirectly by raising the similarity in sectoral specialisation. Through this indirect link, financial integration tends to raise business cycle comovement between countries. JEL Classification: E32, F41, E44financial integration, international business cycle, international transmission of shocks

Do trade and financial linkages foster business cycle synchronization in a small economy?

We estimate a system of equations to analyze whether bilateral trade and financial linkages influence business cycle synchronization directly and/or indirectly. Our paper builds upon the existing literature by using bilateral trade and financial flows for a small, open economy (Spain) as benchmark for the results, instead of the US as generally done in the literature. We find that both the similarity of productive structure and trade links promote the synchronization of cycles. However, bilateral financial links are inversely related to the co movement of output. This might point to financial integration allowing an easiertransfer of resources between two economies, which could enable their decoupling, as predicted by a standard model of international business cycles. Both the effects of trade and financial links on output synchronization are statistically significant and economically relevan

Conformance checking and performance improvement in scheduled processes: A queueing-network perspective

Service processes, for example in transportation, telecommunications or the health sector, are the backbone of today's economies. Conceptual models of service processes enable operational analysis that supports, e.g., resource provisioning or delay prediction. In the presence of event logs containing recorded traces of process execution, such operational models can be mined automatically.In this work, we target the analysis of resource-driven, scheduled processes based on event logs. We focus on processes for which there exists a pre-defined assignment of activity instances to resources that execute activities. Specifically, we approach the questions of conformance checking (how to assess the conformance of the schedule and the actual process execution) and performance improvement (how to improve the operational process performance). The first question is addressed based on a queueing network for both the schedule and the actual process execution. Based on these models, we detect operational deviations and then apply statistical inference and similarity measures to validate the scheduling assumptions, thereby identifying root-causes for these deviations. These results are the starting point for our technique to improve the operational performance. It suggests adaptations of the scheduling policy of the service process to decrease the tardiness (non-punctuality) and lower the flow time. We demonstrate the value of our approach based on a real-world dataset comprising clinical pathways of an outpatient clinic that have been recorded by a real-time location system (RTLS). Our results indicate that the presented technique enables localization of operational bottlenecks along with their root-causes, while our improvement technique yields a decrease in median tardiness and flow time by more than 20%

On the Optimality of a GCC Monetary Union: Structural VAR, Common Trends and Common Cycles Evidence

This paper examines the suitability of the proposed monetary union among the members of the Gulf Cooperation Council (GCC). To do so, we identify the underlying structural shocks that these economies are subject to and assess the extent to which the shocks are symmetric. Additionally, we test for common trends and common business cycles among the GCC economies. We find that while the transitory demand shocks areare typically symmetric, the permanent supply shocks are asymmetric. Furthermore, we do not find synchronous long-run and short-rum movements in output. Despite the progress that has been made in terms of integration, our findings indicate thet the conditions for forming a GCC monetary union have not as yet been met.Gulf Cooperation Council, GCC, optimal monetary union, cointegration,common cycles, structural VAR

AUTOMATED PLANNING OF PROCESS MODELS: THE CONSTRUCTION OF SIMPLE MERGES

Business processes evolve dynamically with changing business demands. Because of these fast changes, traditional process improvement techniques have to be adapted and extended since they often require a high degree of manual work. To reduce this degree of manual work, the automated planning of process models is proposed. In this context, we present a novel approach for an automated construction of the control flow structure simple merge (XOR join). This accounts for a necessary step towards an auto-mated planning of entire process models. Here we build upon a planning domain, which gives us a general and formal basis to apply our approach independently from a specific process modeling lan-guage. To analyze the feasibility of our method, we mathematically evaluate the approach in terms of key properties like termination and completeness. Moreover, we implement the approach in a process planning software and apply it to several real-world processes

Non-contrastive representation learning for intervals from well logs

The representation learning problem in the oil & gas industry aims to construct a model that provides a representation based on logging data for a well interval. Previous attempts are mainly supervised and focus on similarity task, which estimates closeness between intervals. We desire to build informative representations without using supervised (labelled) data. One of the possible approaches is self-supervised learning (SSL). In contrast to the supervised paradigm, this one requires little or no labels for the data. Nowadays, most SSL approaches are either contrastive or non-contrastive. Contrastive methods make representations of similar (positive) objects closer and distancing different (negative) ones. Due to possible wrong marking of positive and negative pairs, these methods can provide an inferior performance. Non-contrastive methods don't rely on such labelling and are widespread in computer vision. They learn using only pairs of similar objects that are easier to identify in logging data. We are the first to introduce non-contrastive SSL for well-logging data. In particular, we exploit Bootstrap Your Own Latent (BYOL) and Barlow Twins methods that avoid using negative pairs and focus only on matching positive pairs. The crucial part of these methods is an augmentation strategy. Our augmentation strategies and adaption of BYOL and Barlow Twins together allow us to achieve superior quality on clusterization and mostly the best performance on different classification tasks. Our results prove the usefulness of the proposed non-contrastive self-supervised approaches for representation learning and interval similarity in particular

Complexity in daily life – a 3D-visualization showing activity patterns in their contexts

This article attacks the difficulties to make well informed empirically grounded descriptions and analyses of everyday life activity patterns. At a first glance, everyday life seems to be very simple and everybody has experiences from it, but when we try to investigate it from a scientific perspective, its complexity is overwhelming. There are enormous variations in interests and activity patterns among individuals, between households and socio-economic groups in the population. Therefore, and in spite of good intentions, traditional methods and means to visualize and analyze often lead to over-simplifications. The aim of this article is to present a visualization method that might inspire social scientists to tackle the complexity of everyday life from a new angle, starting with a visual overview of the individual's time use in her daily life, subsequently aggregating to time use in her household, further at group and population levels without leaving the individual out of sight. Thereby variations and complexity might be treated as assets in the interpretation rather than obstacles. To exemplify the method we show how activities in a daily life project are distributed among household members and between men and women in a population.household division of labour, time-geography, 3D method, visualization, diaries, everyday life, activity patterns. Complexity in daily life – a 3D-visualization showing activity patterns in their contexts