This report analyzes the start-up ecosystem in Tokyo and the greater surrounding area in Japan in the transition of the innovation model to a hybrid of traditional public sector-university-corporation research and development (R and D) combined with start-up agile innovation. It first introduces...

This report analyzes the start-up ecosystem in Tokyo and the greater surrounding area in Japan in the transition of the innovation model to a hybrid of traditional public sector-university-corporation research and development (R and D) combined with start-up agile innovation. It first introduces...

We introduce a high quality proxy for bank misconduct that is constructed from Consumer Financial Protection Bureau (CFPB) complaint data. We employ this proxy to measure the impact of bank misconduct on the expansion of online lending in the United States. Using nearly complete loan and...

A dynamic semi-parametric framework is proposed to study time variation in tail fatness of sovereign bond yield changes during the 2010--2012 euro area sovereign debt crisis measured at a high (15-minute) frequency. The framework builds on the Generalized Pareto Distribution (GPD) for modeling...

Fintech is the application of information technology in the financial sector. In the early days of China’s bond market, treasury bonds were decentralized among intermediaries in paper form, and market chaos occurred frequently. By using information technology, CCDC has enabled...

As a United Nations Sustainable Development Goal (SDG), the global community aims to provide clean and affordable energy to all people by 2030. Despite these efforts, energy poverty remains a reality for billions of people in 2022. Reducing energy poverty is a crucial impediment for public...

A simple methodology is presented for modeling time variation in volatilities and other higher order moments using a recursive updating scheme similar to the familiar RiskMetrics approach. We update parameters using the score of the forecasting distribution. This allows the parameter dynamics to...

We propose a dynamic semi-parametric framework to study time variation in tail parameters. The framework builds on the Generalized Pareto Distribution (GPD) for modeling peaks over thresholds as in Extreme Value Theory, but casts the model in a conditional framework to allow for time-variation...

We propose an empirical framework to assess the likelihood of joint and conditional sovereign default from observed CDS prices. Our model is based on a dynamic skewed-t distribution that captures all salient features of the data, including skewed and heavytailed changes in the price of CDS...

We develop a novel high-dimensional non-Gaussian modeling framework to infer conditional and joint risk measures for many financial sector firms. The model is based on a dynamic Generalized Hyperbolic Skewed-t block-equicorrelation copula with time-varying volatility and dependence parameters...