Economics

We consider a market in which both suppliers and consumers compete for a product via scalar-parameterized supply offers and demand bids. Scalar-parameterized offers/bids are appealing due to their modeling simplicity and desirable mathematical properties with the most prominent being bounded efficiency loss and price markup under strategic interactions. Our model incorporates production capacity constraints and minimum inelastic demand requirements. Under perfect competition, the market mechanism yields allocations that maximize social welfare. When market participants are price-anticipating, we show that there exists a unique Nash equilibrium, and provide an efficient way to compute the resulting market allocation. Moreover, we explicitly characterize the bounds on the welfare loss and prices observed at the Nash equilibrium.

An annual well-being index constructed from thirteen socioeconomic factors is proposed in order to dynamically measure the mood of the US citizenry. Econometric models are fitted to the log-returns of the index in order to quantify its tail risk and perform option pricing and risk budgeting. By providing a statistically sound assessment of socioeconomic content, the index is consistent with rational finance theory, enabling the construction and valuation of insurance-type financial instruments to serve as contracts written against it. Endogenously, the VXO volatility measure of the stock market appears to be the greatest contributor to tail risk. Exogenously, "stress-testing" the index against the politically important factors of trade imbalance and legal immigration, quantify the systemic risk. For probability levels in the range of 5% to 10%, values of trade below these thresholds are associated with larger downward movements of the index than for immigration at the same level. The main intent of the index is to provide early-warning for negative changes in the mood of citizens, thus alerting policy makers and private agents to potential future market downturns.

This paper examines the spatial distribution of income in Ireland. Median gross household disposable income data from the CSO, available at the Electoral Division (ED) level, is used to explore the spatial variability in income. Geary's C highlights the spatial dependence of income, highlighting that the distribution of income is not random across space and is influenced by location. Given the presence of spatial autocorrelation, utilising a global OLS regression will lead to biased results. Geographically Weighted Regression (GWR) is used to examine the spatial heterogeneity of income and the impact of local demographic drivers on income. GWR results show the demographic drivers have varying levels of influence on income across locations. Lone parent has a stronger negative impact in the Cork commuter belt than it does in the Dublin commuter belt. The relationship between household income and the demographic context of the area is a complicated one. This paper attempts to examine these relationships acknowledging the impact of space.

The installation of high-speed rail in the world during the last two decades resulted in significant socioeconomic and environmental changes. The U.S. has the longest rail network in the world, but the focus is on carrying a wide variety of loads including coal, farm crops, industrial products, commercial goods, and miscellaneous mixed shipments. Freight and passenger services in the U.S. dates to 1970, with both carried out by private railway companies. Railways were the main means of transport between cities from the late 19th century through the middle of the 20th century. However, rapid growth in production and improvements in technologies changed those dynamics. The fierce competition for comfortability and pleasantness in passenger travel and the proliferation of aviation services in the U.S. channeled federal and state budgets towards motor vehicle infrastructure, which brought demand for railroads to a halt in the 1950s. Presently, the U.S. has no high-speed trains, aside from sections of Amtrak s Acela line in the Northeast Corridor that can reach 150 mph for only 34 miles of its 457-mile span. The average speed between New York and Boston is about 65 mph. On the other hand, China has the world s fastest and largest high-speed rail network, with more than 19,000 miles, of which the vast majority was built in the past decade. Japan s bullet trains can reach nearly 200 miles per hour and dates to the 1960s. That system moved more than 9 billion people without a single passenger casualty. In this systematic review, we studied the effect of High-Speed Rail (HSR) on the U.S. and other countries including France, Japan, Germany, Italy, and China in terms of energy consumption, land use, economic development, travel behavior, time use, human health, and quality of life.

The main goal of the paper is to extract the aggregate demand and aggregate supply shocks in Greece, Ireland, Italy and Portugal, as well as to examine the correlation among the two types of shocks. The decomposition of the shocks was achieved by using a structural vector autoregression that analyses the relationship between the evolution of the gross domestic product and inflation in the period 1997-2015. The goal of the paper is to confirm the aggregate demand - aggregate supply model in the above-mentioned economies.

Many dynamic microsimulation models have shown their ability to reasonably project detailed population and households using non-data based household formation and dissolution rules. Although, those rules allow modellers to simplify changes in the household construction, they typically fall short in replicating household projections or if applied retrospectively the observed household numbers. Consequently, such models with biased estimation for household size and other household related attributes lose their usefulness in applications that are sensitive to household size, such as in travel demand and housing demand modelling. Nonetheless, these demographic microsimulation models with their associated shortcomings have been commonly used to assess various planning policies which can result in misleading judgements. In this paper, we contribute to the literature of population microsimulation by introducing a fully integrated system of models for different life event where a household alignment method adjusts household size distribution to closely align with any given target distribution. Furthermore, some demographic events that are generally difficult to model, such as incorporating immigrant families into a population, can be included. We illustrated an example of the household alignment method and put it to test in a dynamic microsimulation model that we developed using dymiumCore, a general-purpose microsimulation toolkit in R, to show potential improvements and weaknesses of the method. The implementation of this model has been made publicly available on GitHub.

In the Paris agreement of 2015, it was decided to reduce the CO2 emissions of the energy sector to zero by 2050 and to restrict the global mean temperature increase to 1.5 degree Celcius above the pre-industrial level. Such commitments are possible only with practically CO2-free power generation based on variable renewable technologies. Historically, the main point of criticism regarding renewable power is the variability driven by weather dependence. Power-to-X systems, which convert excess power to other stores of energy for later use, can play an important role in offsetting the variability of renewable power production. In order to do so, however, these systems have to be scheduled properly to ensure they are being powered by low-carbon technologies. In this paper, we introduce a graphical approach for scheduling power-to-X plants in the day-ahead market by minimizing carbon emissions and electricity costs. This graphical approach is simple to implement and intuitively explain to stakeholders. In a simulation study using historical prices and CO2 intensity for four different countries, we find that the price and CO2 intensity tends to decrease with increasing scheduling horizon. The effect diminishes when requiring an increasing amount of full load hours per year. Additionally, investigating the trade-off between optimizing for price or CO2 intensity shows that it is indeed a trade-off: it is not possible to obtain the lowest price and CO2 intensity at the same time.

The global food system faces various endogeneous and exogeneous, biotic and abiotic risk factors, including a rising human population, higher population densities, price volatility and climate change. Quantitative models play an important role in understanding food systems' expected responses to shocks and stresses. Here, we present a stylised mathematical model of a national-level food system that incorporates domestic supply of a food commodity, international trade, consumer demand, and food commodity price. We derive a critical compound parameter signalling when domestic supply will become unsustainable and the food system entirely dependent on imports, which results in higher commodity prices, lower consumer demand and lower inventory levels. Using Bayesian estimation, we apply the dynamic food systems model to infer the sustainability of the UK pork industry. We find that the UK pork industry is currently sustainable but because the industry is dependent on imports to meet demand, a decrease in self-sufficiency below 50% (current levels are 60-65%) would lead it close to the critical boundary signalling its collapse. Our model provides a theoretical foundation for future work to determine more complex causal drivers of food system vulnerability.

Existing emissions trading system (ETS) designs inhibit emissions but do not constrain warming to any fxed level, preventing certainty of the global path of warming. Instead, they have the indirect objective of reducing emissions. They provide poor future price information. And they have high transaction costs for implementation, requiring treaties and laws. To address these shortcomings, this paper proposes a novel double-sided auction mechanism of emissions permits and sequestration contracts tied to temperature. This mechanism constrains warming for many (e.g., 150) years into the future and every auction would provide price information for this time range. In addition, this paper proposes a set of market rules and a bottom-up implementation path. A coalition of businesses begin implementation with jurisdictions joining as they are ready. The combination of the selected market rules and the proposed implementation path appear to incentivize participation. This design appears to be closer to "first best" with a lower cost of mitigation than any in the literature, while increasing the certainty of avoiding catastrophic warming. This design should also have a faster pathway to implementation. A numerical simulation shows surprising results, e.g., that static prices are wrong, prices should evolve over time in a way that contradicts other recent proposals, and "global warming potential" as used in existing ETSs are generally erroneous.

A negative interest rate policy is often accompanied by tiered remuneration, which allows for exemption from negative rates. This study proposes a basic model of interest rates formed in the interbank market with a tiering system. The results predicted by the model largely mirror actual market developments in late 2019, when the European Central Bank introduced, and the Switzerland National Bank modified, the tiering system.