The multiple filter test for change point detection in time series

A framework for the detection of change points in the expectation in sequences of random variables is presented. Specifically, we investigate time series with general distributional assumptions that may show an unknown number of change points in the expectation occurring on multiple time scales and that may also contain change points in other parameters. To that end we propose a multiple filter test (MFT) that tests the null hypothesis of constant expectation and, in case of rejection of the null hypothesis, an algorithm that estimates the change points.The MFT has three important benefits. First, it allows for general distributional assumptions in the underlying model, assuming piecewise sequences of i.i.d. random variables, where also relaxations with regard to identical distribution or independence are possible. Second, it uses a MOSUM type statistic and an asymptotic setting in which the MOSUM process converges weakly to a functional of a Brownian motion which is then used to simulate the rejection threshold of the statistical test. This approach enables a simultaneous application of multiple MOSUM processes which improves the detection of change points that occur on different time scales. Third, we also show that the method is practically robust against changes in other distributional parameters such as the variance or higher order moments which might occur with or even without a change in expectation. A function implementing the described test and change point estimation is available in the R package MFT.     

Structural production layer decomposition: a new method to measure differences between MRIO databases for footprint assessments

Recent empirical assessments revealed that footprint indicators calculated with various multi-regional input–output (MRIO) databases deliver deviating results. In this paper, we propose a new method, called structural production layer decomposition (SPLD), which complements existing structural decomposition approaches. SPLD enables differentiating between effects stemming from specific parts in the technology matrix, e.g. trade blocks vs. domestic blocks, while still allowing to link the various effects to the total region footprint. Using the carbon footprint of the EU-28 in 2011 as an example, we analyse the differences between EXIOBASE, Eora, GTAP and WIOD. Identical environmental data are used across all MRIO databases. In all model comparisons, variations in domestic blocks have a more significant impact on the carbon footprint than variations in trade blocks. The results provide a wealth of information for MRIO developers and are relevant for policy makers designing climate policy measures targeted to specific stages along product supply chains.     

Patterns of vertical specialisation in trade: long-run evidence for 91 countries

Review of World Economics - The authors estimate the domestic value-added content in exports of manufacturing goods (VAX-D ratio) for 91 countries over the period from 1970 to 2013. They find a...     

Sharing versus collaborative economy: how to align ICT developments and the SDGs in tourism?

Great hopes have been placed in the sharing economy to provide a new business model based on peer-to-peer (P2P) exchanges of underutilized assets. As a model, the sharing economy has been expected to make significant contributions to sustainability, providing new opportunities for entrepreneurship, more sustainable use of resources, and consumer co-operation in tight economic networks. However, in recent years, digital platforms have turned into the most important actors in the global sharing economy, turning global corporations, such as AirBnB, Booking, or TripAdvisor into intermediaries controlling and profiting from most transactions. Focused on accommodation, this paper conceptualizes the sharing economy in comparison to the wider collaborative economy, and discusses its social, economic, environmental, and political impacts in comparison to the sustainable development goals. It concludes that the sharing economy has great potential to make very significant contributions to sustainability, though the model is increasingly being replaced by the collaborative economy, which performs as an extension and acceleration of neoliberal economic practices.     

Blockchain in Additive Manufacturing and its Impact on Supply Chains

Additive manufacturing (AM) appears to be a particularly attractive use case for blockchain. This research combines inductive in‐depth interviews with the Delphi method to explore what potentials blockchain technology in AM creates, which adoption barriers firms need to overcome, and how supply chains will be affected by the integration of these two potentially disruptive technologies. The results suggest opportunities that are related to intellectual property (IP) rights management, the monitoring of printed parts throughout their lifecycle, process improvements, and data security. The most important barriers for blockchain adoption in AM are an absence of blockchain‐skilled specialists on the labor market, missing governance mechanisms, and a lack of firm‐internal technical expertise. By addressing important limitations of AM, blockchain is expected to improve the competitiveness of AM in parts’ production, catalyzing the trend toward more decentralized manufacturing resulting in more agile, resilient, and flexible supply chains and reduced logistics costs. Beyond that, blockchain‐based AM platforms are expected to enhance supply chain visibility, drive supply chain digitalization, support supply chain finance, and contribute to the emergence of shared factory systems.     

Fetal Iodine Deficiency and Schooling: A Replication of Field,Robles, and Torero (2009)*

Scholars have theorized that congenital health endowment is an important determinant of economic outcomes later in a person's life. Field, Robles, and Torero (2009, American Economic Journal: Applied Economics 1, 140–169) find large increases in educational attainment caused by a reduction of fetal iodine deficiency following a set of iodine supplementation programs in Tanzania. We revisit the Tanzanian iodine programs with a narrow and wide replication of the study by Field et al. We are able to exactly replicate the original results. We find, however, that the findings are sensitive to alternative specification choices and sample restrictions. We try to address some of these concerns in the wide replication; we increase the sample size fourfold, and we improve the precision of the treatment variable by incorporating new institutional and medical insights. Despite the improvements, no effect is found. We conclude that the available data do not provide sufficient power to detect a possible effect, as treatment assignment cannot be measured with sufficient precision.     

Debating liberalism: Walter Eucken,F. A. Hayek and the early history of the Mont Pèlerin Society

The Review of Austrian Economics - Walter Eucken is mostly known for his impact on establishing the Social Market Economy in post-war Germany. In this paper we identify how Eucken was highly...