The Dragon Stretches its Wings: Assessing the Geopolitical and Economic Implications of China’s Belt and Road Initiative in Pakistan and Kenya

In 2013 China launched what is now known as the Belt and Road Initiative. This multinational, trillion-dollar development project seeks to improve connections by land and sea between China and its economic partners in Asia, Africa, the Middle East, and Europe. Since its launch, many countries have warned that Belt and Road is a thinly-veiled plot for China to advance its geopolitical and military interests. This paper uses Pakistan and Kenya as case studies to assess claims that China is using “debt-trap diplomacy” to accomplish its foreign policy agenda. Using a qualitative and holistic approach, this paper finds that contrary to popular arguments among Western politicians and journalists, most recipient countries are eager to receive Belt and Road investment, and the Initiative has not shown itself to serve China’s military interests. Rather, this paper finds a growing global interest in following Beijing’s models for development and economic growth, despite warnings from the United States and other Western nations

On Prediction Using Variable Order Markov Models

This paper is concerned with algorithms for prediction of discrete sequences over a finite alphabet, using variable order Markov models. The class of such algorithms is large and in principle includes any lossless compression algorithm. We focus on six prominent prediction algorithms, including Context Tree Weighting (CTW), Prediction by Partial Match (PPM) and Probabilistic Suffix Trees (PSTs). We discuss the properties of these algorithms and compare their performance using real life sequences from three domains: proteins, English text and music pieces. The comparison is made with respect to prediction quality as measured by the average log-loss. We also compare classification algorithms based on these predictors with respect to a number of large protein classification tasks. Our results indicate that a "decomposed" CTW (a variant of the CTW algorithm) and PPM outperform all other algorithms in sequence prediction tasks. Somewhat surprisingly, a different algorithm, which is a modification of the Lempel-Ziv compression algorithm, significantly outperforms all algorithms on the protein classification problems