Threshold Effects in Cigarette Addiction: An Application of the Threshold Model in Dynamic Panels

We adopt the threshold model of myopic cigarette addiction to US state-level panel data. The threshold model is used to identify the structural effects of cigarette demand determinants across the income stratification. Furthermore, we apply a bootstrap approach to correct for the small-sample bias that arises in the dynamic panel threshold model with fixed effects. Our empirical results indicate that there exists the heterogeneity of smoking dynamics across consumers.Cigarettes demand, price elasticity, threshold regression model, dynamic panel model, bias correction, bootstrap

Estimating the Impacts of Climate Change on Mortality in OECD Countries

The major contribution of this study is to combines both climatic and macroeconomic factors simultaneously in the estimation of mortality using the capital city of 22 OECD countries from the period 1990 to 2008. The empirical results provide strong evidences that higher income and a lower unemployment rate could reduce mortality rates, while the increases in precipitation and temperature variation have significantly positive impacts on the mortality rates. The effects of changing average temperature on mortality rates in summer and winter are asymmetrical and also depend on the location. Combining the future climate change scenarios with the estimation outcomes show that mortality rates in OECD countries in 2100 will be increased by 3.77% to 5.89%.Climate change; mortality; panel data model

Modeling the Effect of Oil Price on Global Fertilizer Prices

The main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, the autoregressive distributed lag (ARDL) model, and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model, are used to investigate the relationship between crude oil price and six global fertilizer prices. Weekly data for 2003-2008 for the seven price series are analyzed. The empirical results from ARDL show that most fertilizer prices are significantly affected by the crude oil price, which explains why global fertilizer prices reached a peak in 2008. We also find that that the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods, and that the peak crude oil price caused greater volatility in the crude oil price and global fertilizer prices. As volatility invokes financial risk, the relationship between oil price and global fertilizer prices and their associated volatility is important for public policy relating to the development of optimal energy use, global agricultural production, and financial integration.Volatility; Global fertilizer price; Crude oil price; Non-renewable fertilizers; Structural breakpoint unit root test

Online Energy Generation Scheduling for Microgrids with Intermittent Energy Sources and Co-Generation

Microgrids represent an emerging paradigm of future electric power systems that can utilize both distributed and centralized generations. Two recent trends in microgrids are the integration of local renewable energy sources (such as wind farms) and the use of co-generation (i.e., to supply both electricity and heat). However, these trends also bring unprecedented challenges to the design of intelligent control strategies for microgrids. Traditional generation scheduling paradigms rely on perfect prediction of future electricity supply and demand. They are no longer applicable to microgrids with unpredictable renewable energy supply and with co-generation (that needs to consider both electricity and heat demand). In this paper, we study online algorithms for the microgrid generation scheduling problem with intermittent renewable energy sources and co-generation, with the goal of maximizing the cost-savings with local generation. Based on the insights from the structure of the offline optimal solution, we propose a class of competitive online algorithms, called CHASE (Competitive Heuristic Algorithm for Scheduling Energy-generation), that track the offline optimal in an online fashion. Under typical settings, we show that CHASE achieves the best competitive ratio among all deterministic online algorithms, and the ratio is no larger than a small constant 3.Comment: 26 pages, 13 figures. It will appear in Proc. of ACM SIGMETRICS, 201

Single-ancilla ground state preparation via Lindbladians

We design an early fault-tolerant quantum algorithm for ground state preparation. As a Monte Carlo-style quantum algorithm, our method features a Lindbladian where the target state is stationary, and its evolution can be efficiently implemented using just one ancilla qubit. Our algorithm can prepare the ground state even when the initial state has zero overlap with the ground state, bypassing the most significant limitation of methods like quantum phase estimation. As a variant, we also propose a discrete-time algorithm, which demonstrates even better efficiency, providing a near-optimal simulation cost for the simulation time and precision. Numerical simulation using Ising models and Hubbard models demonstrates the efficacy and applicability of our method