Machine learning in individual claims reserving

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving.     

Multi-product capacitated facility location problem with general production and building costs

This research introduces the multi-product capacitated facility location problem with general production and building costs (MP-CFLPGC). The MP-CFLPGC extends previous problems found in the literature by including multiple products and general production and building cost functions that allow the modeling of different behaviors like economies of scale and congestion. The MP-CFLPGC is formulated as a mixed integer linear program (MILP). To evaluate the performance of the proposed formulation we analyze the results of a commercial optimizer on a set of 288 randomly generated test instances that resemble the Colombian cement industry supply chain. After one hour the optimizer achieved an optimality gap of 1.0 % or less in 55 % out of the 288 test instances. On average the optimality gap was 3.57 %. Additionally, we propose a randomized mathematical-programming-based heuristic for the test instances where the MILP formulation presents significantly high optimality gaps.     

The Adjusted Big Mac Methodology: A Clarification

The Economist's adjusted Big Mac index takes GDP into account in currency valuation, but the methodology is not explained. We show that the key to understanding the methodology is to distinguish between a currency's bilateral valuation (versus a specific currency) and the currency's overall valuation (versus a “basket” of a large number of currencies). Also, the adjusted Big Mac estimates of intrinsic foreign exchange (FX) rates have been better forecasts of actual FX changes than those of the original “raw” Big Mac index.     

Cooperation with a multiproduct corporation in a strategic managerial delegation

We consider an industry composed of a multiproduct corporation that adopts corporate social responsibility (CSR) as a strategic managerial delegation and examine the profit-incentive to form a cooperative group. We find that competition is an equilibrium for any degree of substitutability and yields the highest CSR, which is increasing in the degree of substitutability. We also show that full cooperation is an equilibrium for lower substitutability but induces no CSR, whereas partial cooperation with one uniplant firm is an equilibrium for higher substitutability but yields lower CSR than that under competition. Therefore, cooperation might reduce strategic CSR activities, whereas competition will encourage higher CSR but yield lower industry profits.     

Microfoundations of companies' dynamic capabilities for environmentally sustainable innovation: Case study insights from high‐tech innovation in science‐based companies

To achieve sustainable development, companies are increasingly putting an emphasis on the creation and the promotion of environmentally sustainable innovations. Environmentally sustainable innovation often involves a significant shift in a new strategic direction. This paper studies this shift from a dynamic capabilities perspective and aims to identify the microfoundations of science‐based companies' dynamic capabilities for high‐tech environmentally sustainable innovations. It investigates the development of high‐tech environmentally sustainable innovations in two distinctive science‐based companies. To scholars, this study provides an in‐depth process analysis, over time, of how and why microfoundations of dynamic capabilities influence the development of a science‐based company's high‐tech environmentally sustainable innovations. To practitioners in science‐based firms, this process study can function as a frame of reference, enabling the tailoring of a strategy for high‐tech environmentally sustainable innovation.     

Prediction regions for interval-valued time series

We approximate probabilistic forecasts for interval-valued time series by offering alternative approaches. After fitting a possibly non-Gaussian bivariate vector autoregression (VAR) model to the center/log-range system, we transform prediction regions (analytical and bootstrap) for this system into regions for center/range and upper/lower bounds systems. Monte Carlo simulations show that bootstrap methods are preferred according to several new metrics. For daily S&P 500 low/high returns, we build joint conditional prediction regions of the return level and volatility. We illustrate the usefulness of obtaining bootstrap forecasts regions for low/high returns by developing a trading strategy and showing its profitability when compared to using point forecasts.     

Italy’s Political Upheaval and the Consequences of Inequality

Intereconomics - Political upheaval, with the dangerous rise of the far right – in Italy and Europe – is likely to be stabilised when politics and policies again turn their attention to...