Paper analyzes patterns in African exports using network analysis.
problem Limited data on African countries in trade networks.
method Defined two bipartite networks and their minimal spanning trees.
result Emerging patterns reveal important characteristics of African exports.
What are East Africa's industrial opportunities? In this article we explore this question by using the Product Space to study the productive structure of five south-east African countries: Kenya, Mozambique, Rwanda, Tanzania and Zambia. The Product Space is a network connecting products that tend to be exported by the …
Trains neural machine translation models for 5 Southern African languages.
problem Lack of shared resources and reproducible results for African languages.
method Trained neural machine translation models on publicly-available datasets.
result Provides code for training and evaluating models, aiming to spur future research.
Neural machine translation models trained for 5 South African languages.
problem Lack of resources and research for machine translation in African languages.
method Training neural machine translation models for 5 South African languages using modern techniques.
result Promises of neural machine translation for African languages.
Local logarithmic export distributions show non-zero skewness that changes with exporter and destination characteristics.
problem Identifying the skewness in local logarithmic export distributions and its relationship with exporter and destination characteristics.
method Analyzing directed links weighted by the logarithm of export values, studying the skewness of local exports, and formulating quantitative relations.
result Non-zero skewness in local logarithmic export distributions changes with exporter and destination characteristics.
The abstract covers various aspects of eBusiness and eGovernment, including digital currencies, m-government services, gender inclusivity, eLearning, export performance, SME digitalization, and banking customer behavior.
problem Various challenges and opportunities in eBusiness and eGovernment.
method Critical review, UTAUT model with perceived risk theory, GAD approach, inductive research paradigm, one-on-one interviews, survey questionnaires, convenience sampling.
result Impediments to eLearning uptake, gender inclusivity in e-procurement, export performance of manufacturing firms, SME digitalization impact, measuring and modeling framework for Internet banking customers.
East African tech experts identify machine learning challenges.
problem Machine learning research needs in East African tech industry.
method 46 interviews with tech professionals.
result Concrete machine learning problems identified.
Paper aims to improve education online in South Africa using NMT for Setswana.
problem Inclusion of machine translation for low-resourced local languages in online education.
method Demonstrates state-of-the-art performance on English-to-Setswana translation using the Transformer architecture.
result Current NMT techniques show promise for African languages, beating previous methods by 5.33 BLEU points.
SAGDA generates synthetic agricultural datasets to improve ML in African farming.
problem Data scarcity in African agriculture limits machine learning innovations.
method SAGDA is an open-source Python toolkit that generates, augments, and validates synthetic agricultural datasets.
result SAGDA enhances ML applications in agriculture, such as yield prediction and fertilizer recommendation.
COMPAS recidivism predictions show racial bias against African Americans, study finds.
problem Racial bias in recidivism prediction algorithms.
method Causal analysis using FACT, a fairness measure grounded in causal inference.
result COMPAS shows racial bias against African American defendants, robust to unmeasured confounding.
This study analyzes Peru's export performance using a gravity model.
problem Understanding factors affecting Peru's export performance.
method Augmented gravity model of trade, panel data analysis.
result Positive coefficients for economic size, negative for distance.
The highly detailed international trade data among all countries in the world during 1971-2000 shows that the kinds of export goods and the logarithmic GDP (gross domestic production) of a country has an S-shaped relationship. This indicates all countries can be divided into three stages accordingly. First, the poor co…
Export bans during pandemic worsen medical supply shortages globally.
problem Impact of export restrictions on medical goods during pandemic.
method Model of shock diffusion through international trade network.
result Export bans are counterproductive, making most countries worse off.
Proposes deep feature selection for HTN risk factors in African-Americans.
problem Identifying significant risk factors for heart damage in African-Americans with hypertension.
method Uses stacked auto-encoders for feature learning and representation in deep architecture.
result Deep learning approach leads to better results in identifying LVMI risk factors.
Study shows social influence significantly impacts mobile app adoption in African app stores.
problem Understanding social influence on mobile app choices in app stores.
method Developed a structural model combining diffusion and choice models, used Bayesian estimation.
result Customer choices explained better by offline social influence than online density.
Study analyzes Colombian firms' export capabilities over 5 years.
problem Understanding specialization in Colombian firms' export products.
method Bipartite network analysis, modularity maximization, Louvain algorithm.
result Firms specialize in exporting specific product categories, forming clusters.
The study finds that the export shares of machinery and food/crude materials are significantly correlated with GDP.
problem Understanding the relationship between export shares and GDP across different commodity sectors.
method Analysis of GDP and international trade data using the SITC classification from 1962 to 2000.
result The export shares of machinery and food/crude materials are significantly correlated with GDP, following a power-law relationship.
Develops a tool to measure gradual internationalization performance.
problem Lack of objective performance indicators for gradual internationalization.
method Quantitative tool based on export data, tested in Spanish wine sector.
result Creation of an international priority index for analyzing geographically differentiated strategies.
Framework simulates systemic risk in South African banking sector.
problem Monitoring systemic risk in banking systems.
method Network-based approach considering shock propagation and systemic market risks.
result Simulated systemic risk spikes align with subjective assessments.
SUBIC detects patient subgroups for personalized treatment of HTN in African-Americans.
problem Developing tailored treatment schemes for different patient subgroups.
method Supervised Biclustering using convex optimization.
result Identifies and prioritizes risk factors for HTN in African-Americans.
Spain uses DEA to select international markets for exports.
problem Choosing the best international markets for Spanish exports.
method Output-oriented DEA model considering multiple validated inputs and outputs.
result Identifies efficient regions generating higher benefits with lower costs.
Study compares market microstructure between two South African exchanges.
problem Understanding price response dynamics and market microstructure differences between two South African exchanges.
method Comparative analysis of returns distributions, auto-correlations, price impact, and trading costs on different time scales.
result Similar stylized facts emerge as measurement time scale increases, but price responses vary significantly.
Model uses HS-FP framework for South African asset allocation.
problem Develops a flexible non-parametric asset allocation model for South African markets.
method Historical Simulation with Flexible Probabilities (HS-FP) framework, using relative entropy for distribution estimation.
result HS-FP model outperforms classic MVO and EW benchmarks in out-of-sample performance.
In this paper, we analyse the South African implied volatility in various setting. We assess the information content in SAVI implied volatility using daily markets data. Our empirical application is focused on the FTSE/JSE Top 40 index and we emphasize our models performance in distinct sub-periods. Our results are com…
Few attempts have been proposed in order to describe the statistical features and historical evolution of the export bipartite matrix countries/products. An important standpoint is the introduction of a products network, namely a hierarchical forest of products that models the formation and the evolution of commodities…
Economies grow by upgrading the type of products they produce and export. The technology, capital, institutions and skills needed to make such new products are more easily adapted from some products than others. We study the network of relatedness between products, or product space, finding that most upscale products a…
With this work it is analyzed the import and export of horticultural products between Portugal and the other world countries. It is used data about Portuguese international trade of vegetables from 2006 to 2010. The data were obtained from the INE (Statistics Portugal), gently given by the AICEP (Trade & Investment Age…
Credit expansion led to stronger household leverage cycles during the U.S. business cycle.
problem Understanding the role of credit supply in the U.S. business cycle.
method Causal evidence from 1999-2010 U.S. business cycle data.
result Credit expansion, particularly in private-label mortgages, caused stronger household leverage cycles.
REGOMAX analyzes EU economies' sensitivity to petroleum and gas trade from major exporters.
problem Analyzing EU economies' sensitivity to petroleum and gas trade from major exporters.
method Reduced Google matrix (REGOMAX) algorithm applied to UN COMTRADE data.
result Shows sensitivity of each EU country to petroleum and gas trade from Russia, USA, Saudi Arabia, and Norway.
Model reconstructs and simulates international trade networks under policy changes.
problem Reconstructing and simulating international trade networks under policy changes.
method Maximizing entropy based on local trade information to reconstruct networks; simulating structural changes using trade tariffs.
result Trade networks can be successfully reconstructed and simulated under policy changes.
This work uses a recommendation system to enhance exporting countries' fitness.
problem Predicting and optimizing the evolution of international trade networks.
method A recommendation system was used to identify overlooked products for countries.
result Countries can improve their national competitiveness by diversifying exported products.
We investigate the relative market efficiency in financial market data, using the approximate entropy(ApEn) method for a quantification of randomness in time series. We used the global foreign exchange market indices for 17 countries during two periods from 1984 to 1998 and from 1999 to 2004 in order to study the effic…
Countries rarely enter unrelated products, but those that do grow faster.
problem Understanding the benefits of entering unrelated products for economic growth.
method Identifying periods of unrelated product entry through analysis of 93 countries' exports from 1965 to 2014.
result Countries entering more unrelated products experience a small but significant increase in future economic growth.
Paper presents mdfa to identify victims of discrimination in black box classifiers.
problem Identifying victims of discrimination in black box classifiers.
method Reduces discrimination measurement to matching distributions and sensitive attribute coincidence prediction.
result Identifies African-American individuals at high risk of violent recidivism.
Unified theory explains housing cycle across metros, showing credit expansion impacts.
problem Puzzling correlations between income and mortgage growth across ZIP codes and metros.
method Unified credit expansion theory, double differences, instrumental variables.
result Credit expansion drives housing cycle, affecting boom, bust, and recovery phases.
Study predicts global trade impacts using deep learning during the COVID-19 period.
problem Forecasting global trade impacts during the COVID-19 pandemic.
method Developed a sustainable prediction process using Long-Short Term Memory (LSTM) deep learning model.
result Accurately predicted daily imports and exports for the next 180 days during the pandemic.
LSTMs outperform DFM in nowcasting COVID-19 economic variables.
problem Timely estimation of macroeconomic variables during the pandemic.
method Comparison of LSTM and DFM performance on three variables (export values, volumes, and services exports).
result LSTMs outperformed DFM in two-thirds of variable/quarter combinations.
Within the last two decades, Foreign Direct Investment (FDI) has been observed as one of the prime instruments in the process of restructuring the European economies in transition. Many scholars argue that FDI is expected to be a source of valuable technology transfer thus might certainly have positive effects on host …
Predicting the future evolution of complex systems is one of the main challenges in complexity science. Based on a current snapshot of a network, link prediction algorithms aim to predict its future evolution. We apply here link prediction algorithms to data on the international trade between countries. This data can b…
This work is the first part of a project dealing with an in-depth study of effective techniques used in econometrics in order to make accurate forecasts in the concrete framework of one of the major economies of the most productive Italian area, namely the province of Verona. In particular, we develop an approach mainl…
This paper uses open data to analyze foreign tourists' spending patterns in Colombia and the Netherlands.
problem Difficulty in identifying which domestic industries cater to foreign visitors.
method Use of open source data and anonymized transaction data to map tourist destinations and analyze spending behavior.
result Countries may observe different tourist patterns (concentration vs decentralization).
Much of the analysis of economic growth has focused on the study of aggregate output. Here, we deviate from this tradition and look instead at the structure of output embodied in the network connecting countries to the products that they export.We characterize this network using four structural features: the negative r…
Study the structure of international trade through hypergraphs.
problem Understanding the complex relationships in international trade networks.
method Analyzing the mean hyperdegree of adjacent vertices and decomposing correlation properties.
result Identifies bias in trade relationships not visible in pairwise networks.
Proposes a new method for determining LGD discount rates based on cost of capital.
problem Determining an appropriate discount rate for LGD estimation.
method Market-consistent pricing of defaulted loan portfolios to infer discount rates.
result Discount rates reflect both undiversifiable risk and time value of money.
Study uses Google matrix analysis to show how COVID-19 changed international trade flows.
problem Impact of COVID-19 on international trade patterns.
method Google matrix analysis of World Trade Network (WTN), including PageRank, CheiRank, and reduced Google matrix.
result Significant changes in international trade flows due to the pandemic, affecting export and import balances.
We redefine SICR-events for better loan classification under IFRS 9.
problem Ambiguity in SICR-event definition under IFRS 9.
method Proposed alternative framework with three parameters: delinquency, stickiness, and outcome period. Varying these parameters, we generated 27 unique SICR-definitions and fitted logistic regression models.
result The proposed SICR-models outperform the PD-comparison approach as an early-warning system for credit losses.
Using the United Nations COMTRADE database \cite{comtrade} we construct the Google matrix G of multiproduct world trade between the UN countries and analyze the properties of trade flows on this network for years 1962 - 2010. This construction, based on Markov chains, treats all countries on equal democratic grounds …
Bayesian hierarchical tensor factorization model for international trade flows
problem Sparse semi-continuous tensor data modeling
method Bayesian hierarchical tensor factorization with Poisson and Gamma models
result Identifies multiway dependence in trade flows